effects of spectral modification on perceived brightness

The Pennsylvania State University

The Graduate School

Department of Architectural Engineering

EFFECTS OF SPECTRAL MODIFICATION ON PERCEIVED BRIGHTNESS AND

COLOR DISCRIMINATION

A Thesis in

Architectural Engineering

by

Minchen Wei

2011 Minchen Wei

Submitted in Partial Fulfillment of the Requirements

for the Degree of

Master of Science

August 2011

ii

The thesis of Minchen Wei was reviewed and approved* by the following:

Kevin W. Houser

Associate Professor of Architectural Engineering

Thesis Advisor

Richard G. Mistrick


Jelena Srebric


Linda M. Hanagan

Associate Professor and Chair of Graduate Program of Architectural Engineering

*Signatures are on file in the Graduate School

iii

Abstract

This study characterized the effect of spectral modification on perceived brightness and color

discrimination under illumination provided by a pair of 32W, 4-foot, linear fluorescent lamps:

SPX 3000K (SPK3K) and the Reveal® linear fluorescent (RevLF). Sixty subjects participated,

with half 25 years or younger (mean = 22.5, std. dev. = 1.7) and half 60 years or older (mean =

81.4, std. dev. = 7.1).

The side-by-side evaluation mode was employed to characterize perceived brightness. Subjects

made a forced choice for each of 44 pairs of light settings that: were practice trials (4 pairs);

differed in spectrum at equal illuminance (8 pairs); varied in both spectrum and illuminance (24

pairs); or were identical (i.e. null condition trials, 8 pairs). Light settings were set within a range

of 240 to 330 lux and the rooms had neutral gray surfaces. Equal perceived brightness was

inferred from the paired comparisons, and found to occur when the photopic quantity (e.g.

illuminance, luminance) from the RevLF was 5% lower (younger subjects) or 8% lower (older

subjects) than that provided by the SPX3K lamps.

At equal illuminance of 330 lux, the room illuminated by the RevLF was preferred to the one

illuminated by the SPX3K by 67% of the younger subjects and 73% of the older subjects. Color

and brightness were most commonly cited as reasons for preference.

Color discrimination was characterized under 300 lux of RevLF and SPX3K illumination using

the Farnsworth-Munsell 100 Hue Test (FM-100). For color-normal people below 25 years of age,

and for those above 60 years of age who had cataract surgery, the red-green partial error score

was statistically better under RevLF illumination. A significant difference was not found in the

blue-yellow partial error score or in the total error score.

iv

When brightness perception is considered in isolation, the spectral advantages of the RevLF

cannot be offset by the disadvantage of lower luminous efficacy. That is, these data suggest that

at equal brightness a room illuminated with RevLF will consume more energy than an otherwise

identical room illuminated with SPX3K. When brightness and color discrimination are considered

together, as with visual clarity, it is unknown whether RevLF or SPX3K illumination would be

more energy efficient. Color discrimination, brightness perception, and overall preference all play

a role in occupants‘ gestalt evaluation, contribute to high performance building interiors, and play

a role in sustainable lighting solutions designed to address occupant needs.

v

TABLE OF CONTENTS

LIST OF FIGURES ..................................................................................................................... vii

LIST OF TABLES ........................................................................................................................ xi

Acknowledgements ..................................................................................................................... xiii

Chapter 1 Introduction.................................................................................................................. 1

1.1 Background ................................................................................................................................ 1

1.1.1 The Human Eye ...................................................................................................................... 1

1.1.2 Color ....................................................................................................................................... 6

1.1.3 Theories of Color Vision ...................................................................................................... 12

1.1.4 Changes with Age ................................................................................................................. 15

1.2 Objective .................................................................................................................................. 18

1.3 General Approach .................................................................................................................... 19

Chapter 2 Literature Review ...................................................................................................... 20

2.1 Lamp SPD Vs. Spatial Brightness ........................................................................................... 20

2.2 Experimental Methods for Brightness Perception ................................................................... 28

2.3 Color Discrimination ............................................................................................................... 30

2.4 Spectral Modification ............................................................................................................... 33

Chapter 3 Design of the Study and Methodology ..................................................................... 36

3.1 Apparatus ................................................................................................................................. 36

3.2 Subjects .................................................................................................................................... 39

3.3 Independent Variables ............................................................................................................. 40

3.3.1 Independent Variables for Perceived Brightness .................................................................. 40

3.3.2 Independent Variables for Color Discrimination .................................................................. 47

3.4 Dependent Variables ................................................................................................................ 47

vi

3.4.1 Dependent Variables for Perceived Brightness..................................................................... 47

3.4.2 Dependent Variables for Color Discrimination .................................................................... 47

3.5 Statistical Design ..................................................................................................................... 48

3.5.1 Statistical Design for Perceived Brightness .......................................................................... 48

3.5.2 Statistical Design for Color Discrimination .......................................................................... 51

3.6 Experimental Procedures ......................................................................................................... 51

Chapter 4 Analysis and Results .................................................................................................. 54

4.1 Data Reliability: Null Condition Trials and Tests for Bias ...................................................... 54

4.2 Perceived Brightness ................................................................................................................ 58


Chapter 5 Discussion ................................................................................................................... 77

5.1 Perceived Brightness ................................................................................................................ 77


Chapter 6 Conclusions ................................................................................................................. 91

Reference ...................................................................................................................................... 92

vii

LIST OF FIGURES

Figure 1-1 | A drawing of a section through the human eye [1] .............................................. 1

Figure 1-2 | A simple diagram of the organization of the retina [1] ........................................ 3

Figure 1-3 | Distribution of rods and cones in the retina [4] .................................................... 3

Figure 1-4 | Luminous efficiency functions recognized by CIE [8] ........................................ 5

Figure 1-5 | Normalized cone fundamentals and photopigment sensitivities [8] ..................... 6

Figure 1-6 | RGB color matching functions [8] ....................................................................... 8

Figure 1-7 | XYZ color matching functions [8] ....................................................................... 8

Figure 1-8 | The CIE 1976 USC with isotemperature lines ..................................................... 9

Figure 1-9 | Organization of Munsell Color System ................................................................ 11

Figure 1-10 | A possible diagram of the opponent system ....................................................... 14

Figure 1-11 | Opponent signals from the possible model of the opponent system (the

functions are linear transformation of CMFs) [8] .................................................................... 14

Figure 1-12 | The Change of pupil diameter with age [1] ........................................................ 16

Figure 1-13 | The change of absorbance of lens with age [1] .................................................. 17

Figure 1-14 | The transmission of the human donor lenses with age [18] ............................... 17

Figure 1-15 | Spectral power distribution of the SPX3K and the RevLF, adjusted so that

peak relative output is at 100% ................................................................................................ 18

Figure 2-1 | Chromaticity diagram of the locations of ten lamps and the average B/L

ratios [23] ................................................................................................................................. 21

Figure 2-2 | B/L ratio contours on the 1931CIE chromaticity diagram [25] ............................ 23

viii

Figure 2-3 | Section of the CIE 1931 chromaticity diagram including 16 lamps whose

chromaticity coordinates were close to the blackbody locus and B/L ratio versus CCT

[23] ........................................................................................................................................... 23

Figure 2-4 | Relationship between brightness and CCT. (a) Percentage of subjects

selecting 3500K lamps over 6500K lamps in side-by-side comparisons; (b) Mean

adjusted illuminance and standard deviations for two pairs of comparisons in the

brightness matching trials [28] ................................................................................................. 24

Figure 2-5 | Ratio of power of lights to total power (Left: ratio of the power of light at

variable wavelength to total power. Right: ratio of the power of two primary lights to

total power) Red lines indicate the wavelengths require less power, and blue lines

indicate the wavelengths require more power [33] .................................................................. 26

Figure 2-6 | Total Error Score (TES) of FM-100 versus the illuminance level for different

age groups [67] ........................................................................................................................ 32

Figure 2-7 | Color discrimination performance of FM-100 for each age group and

illuminance level [69] .............................................................................................................. 33

Figure 2-8 | Transmittance of the lens used for spectral modification [71] ............................. 34

Figure 3-1 | Photograph of the installation of the lamps, luminaires and baffles .................... 37

Figure 3-2 | A view from behind the subject‘s seated position in the session on perceived

brightness ................................................................................................................................. 38

Figure 3-3 | A view from behind the subject‘s seated position in the session on color

discrimination .......................................................................................................................... 39

Figure 3-4 | The SPDs of the two stimuli – the SPX3K and the RevLF - each an average

of measurements ...................................................................................................................... 41

Figure 3-5 | Photograph of the calibration during the course of the experiment...................... 45

ix

Figure 3-6 | Chromaticity coordinates plotted in the 1931 CIE chromaticity diagram for

all measurements. The coordinates for each measurement can be enclosed by a four-step

MacAdam Ellipse. The measurements were taken at different times during the course of

the experiment for one of the light settings in one room each time ......................................... 46

Figure 3-7 | Example of light settings provided for counter-balance ....................................... 50

Figure 4-1 | Example of Chi-Squared test of independence between SPD and location

(results for all the pairs are summarized in Table 4-2) ............................................................ 56

Figure 4-2 | Plot of percentage of votes versus illuminance ratios at different illuminance

levels of SPX3K for younger group (a. 240 lux; b. 270 lux; c. 300 lux; d. 330 lux) ............... 60


levels of SPX3K for older group (a. 240 lux; b. 270 lux; c. 300 lux; d. 330 lux) ................... 61

Figure 4-4 | Plot of percentage of votes versus illuminance ratios (a. younger age group;

b. older age group) ................................................................................................................... 63


levels of SPX3K for the older subjects without cataract surgery (a. 240 lux; b. 270 lux; c.

300 lux; d. 330 lux) .................................................................................................................. 66


levels of SPX3K for the older subjects with cataract surgery (a. 240 lux; b. 270 lux; c.

300 lux; d. 330 lux) .................................................................................................................. 67

Figure 4-7 | Plot of percentage of votes versus illuminance ratios (a. older subjects

without cataract surgery; b. older subjects with cataract surgery) ........................................... 70

Figure 4-8 | The mean Total Error Score (TES), Red-Green Partial Error Score (R-G

PES), and Blue-Yellow Partial Error Score (B-Y PES) of the subjects with normal color

x

vision in each age group for the FM-100 under each light setting, shown with individual

95% confidence interval bars ................................................................................................... 72

Figure 4-9 | The mean Total Error Score (TES), Red-Green Partial Error Score (R-G

PES), and Blue-Yellow Partial Error Score (B-Y PES) of the subjects in older group for

the FM-100 under each light setting, shown with individual 95% confidence interval bars. .. 76

Figure 5-1 | Neural Opponent Signals & SPDs of two lamps .................................................. 77

Figure 5-2 | Opponent signals adapted to the SPX3K and the RevLF ( a. Red-green

opponent signal; b. Blue-yellow opponent signal ) .................................................................. 78

Figure 5-3 | FM Gamut Area shown in the CIE 1960 UCS for the RevLF, the SPX3K,

and CIE Illuminant C ( Illuminant C is the reference source under which the samples

have approximately equal spacing) .......................................................................................... 87

Figure 5-4 | Plots of the chromaticity coordinates of FM sample 14 to sample 33 lit by the

RevLF and the SPX3K in the CIE 1960 UCS ......................................................................... 88

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LIST OF TABLES

Table 1-1 | Luminous efficiency functions for different usages .............................................. 5

Table 1-2 | Properties of the SPX3K and the RevLF in GE Catalog [19] ................................ 19

Table 2-1 | Studies giving reliable results of SPD effect on brightness [49] ........................... 29

Table 3-1 | Demographic summary of the subjects. (Of the 3 subjects in the older group

with abnormal color vision, all of them had had cataract surgery) .......................................... 40

Table 3-2 | Characterization of the average SPDs for the SPX3K and the RevLF .................. 42

Table 3-3 | Horizontal illuminance programmed for the SPX3K and the RevLF .................... 43

Table 3-4 | Summary information of light settings and nominal calibration characteristics.

Both rooms required and identical set of light setting, for a total of 28 light settings, each

corresponding to a scene programmed into one of the two Lutron Grafik Eye® controllers ... 43

Table 3-5 | Average and standard deviation of the illuminance of the light settings

measured in each room ............................................................................................................ 45

Table 4-1 | Summary data for null condition trials showing percentages of left/right

selected. None of the trials in either age group had a p-value smaller than 0.05; p-values

are only shown for the overall (i.e. age group pooled) category.............................................. 55

Table 4-2 | Summary of results for Chi-Squared test of independence. The SPD and

location are statistically independent (p-value>0.05) .............................................................. 57

Table 4-3 | Percentage of votes in younger group at different illuminance levels of

SPX3K ..................................................................................................................................... 59

Table 4-4 | Percentage of votes in older group at different illuminance levels of SPX3K (

The shaded cells in emboldened values represent results that are not statistically different

from chance according to the Chi-Square Goodness-of-Fit test with p-values > 0.05) ........... 59

xii

Table 4-5 | Summary of the regression lines and hypothesis testing for the plots of

younger and older groups ......................................................................................................... 62

Table 4-6 | Percentage of votes of 10 older subjects without cataract surgery at different

illuminance levels of SPX3K ................................................................................................... 64

Table 4-7 | Percentage of votes of 20 older subjects with cataract surgery, including three

with abnormal color vision, at different illuminance levels of SPX3K ................................... 65

Table 4-8 | Summary of the regression lines and hypothesis testing for the plots of

subjects with and without cataract surgery .............................................................................. 68

Table 4-9 | Summary of the results of FM-100 of the subjects with normal color vision in

each age group under each light setting ................................................................................... 71

Table 4-10 | Analysis of variance for R-G PES ....................................................................... 73

Table 4-11 | Analysis of Variance for B-Y PES ...................................................................... 73

Table 4-12 | Analysis of Variance for TES .............................................................................. 73

Table 4-13 | Summary of the results of Student‘s Paired Sample t-tests ................................. 74

Table 4-14 | Summary of the results of FM-100 of the color-deficient subjects in each age

group under each light setting .................................................................................................. 75

Table 5-1 | Lighting metrics and colorimetric properties of two SPDs. The calculations

were based on the average SPDs. ............................................................................................ 79

Table 5-2 | Standard deviations of the caps of three SPDs ...................................................... 88

xiii

Acknowledgements

I want to express my sincere thanks to the following people, without whom my research

would not have been finished:

Dr. Kevin Houser Dr. Richard Mistrick

Dr. Jelena Srebric Dr. Michael Royer

Andrea Wilkerson Craig Casey

Tony Esposito Yi Wei

Fengzhi Zhang

Dr. Kevin Houser, my advisor, who gave me the opportunity to participate in this project,

taught me how to do research, supported me to finish the project, and also serves as a

model for my professional career.

Dr. Richard Mistrick, who taught me a lot of knowledge in the lighting field outside my

research area and gave me good guidance on my project.

Dr. Jelena Srebric, who is my committee member and gave me good suggestions about

my research.

Dr. Michael Royer, Andrea Wilkerson, and Craig Casey, my good colleagues at Penn

State, who helped me a lot and gave me very good advice about my research and study

over the last two years. Tony Esposito, project assistant, who assisted me with apparatus

modification and data collection.

My father and mother, for supporting me unconditionally in China.

*This research was funded by GE Lighting.

1

Chapter 1 Introduction

1.1 Background

1.1.1 The Human Eye

The electromagnetic spectrum is the range of all possible frequencies of electromagnetic

radiation, covering from short wavelength to long wavelength. However, not all the wavelengths

are visible to the human visual system. Visible light is only a small part of the electromagnetic

spectrum, from 380nm to 780nm.

The light reflected from an object to our eyes enables us to see the object. The eye is the place

where vision begins. As shown in Figure 1-1, the eye consists of the lens, cornea, pupil, fovea,

and the retina. There are different kinds of photoreceptors in the retina, which connect at the back

of the eye. When the light enters the eye through the pupil, it passes through the transparent

cornea and lens, which creates a focused image on our retina. The light in the image on the retina

stimulates the photoreceptors. The fovea on the retina is of particular interest, as it has the most

acute vision of the entire retina.

Figure 1-1 | A drawing of a section through the human eye [1]

2

There is a kind of electrically excitable cell that can process and transmit information by

electrical and chemical signaling in our body, called a neuron. A photoreceptor is a specialized

type of neuron found in the retina, converting visible light into signals that can stimulate

biological processes. Rods and cones are the two classic photoreceptors in the retina, which are

part of the visual system. A third kind of photoreceptor was found in 2002 [2], intrinsically

photosensitive retina ganglion cell (ipRGC), which establishes a relationship between

neurophysiology and circadian photobiology.

Rods and cones are found in the photoreceptor layer of the retina and the names of them are

derived from their shapes [3]. Both of these photoreceptors contain light-sensitive chemicals

called photopigments, which react to light and trigger electrical signals. These signals flow

through a network of neurons and eventually reach the back of the eye in the optic nerve, which

conducts signals toward the brain. Figure 1-2 shows the organization of the retina. The fovea is

the most acute area in the retina, which only contains cones. The peripheral retina, which is the

entire area of the retina outside the fovea, contains both cones and rods. However, the blind spot

is the place in the retina that does not contain any photoreceptor. The distribution of the rods and

cones in the retina is shown in Figure 1-3.

3

Figure 1-2 | A simple diagram of the organization of the retina [1]

Figure 1-3 | Distribution of rods and cones in the retina [4]

4

The most important distinction between rods and cones is the visual function. Rods serve vision

at lower luminance levels (below 0.01 cd/m2), while cones serve vision at higher luminance levels

(above 3.0 cd/m2). At the luminance level between 0.01 cd/m2 and 3.0 cd/m2, both rods and cones

function simultaneously. The vision when only cones are active is called photopic vision, while

only rods are active is called scotopic vison. And mesopic vision is the vision in which both cones

and rods are active [4]. Cones are able to provide chromatic vision, which helps us to discriminate

different colors, while rods only provide achromatic vision.

Besides visual function, rods and cones have different spectral sensitivity to light with different

wavelengths. A lot of studies and experiments have been done to investigate the luminous

efficiency function. 𝑉(𝜆), the luminous efficiency function for photopic vision, describes the

efficiency of radiant flux at stimulating the cones in the eye, which has a peak wavelength at

555nm. 𝑉′(𝜆), the luminous efficiency function for scotopic vision, describes the efficiency of

radiant flux at stimulating the rods in the eye, which has a peak wavelength at 507nm. Since 𝑉(𝜆)

is only valid for small filed view of about 2º, CIE developed some other spectral luminous

efficiency functions for different conditions, which are listed in Table 1-1 and shown in Figure

1-4. 𝑉 ′(𝜆) was measured when the visual angles were not less than 5º. With the combination of

rods and cones, the luminous efficiency function for mesopic vision is complex. The unified

System of Photometry (USP-system) [5], Mesopic Optimization of Visual Efficiency (MOVE-

system) [6], and Intermediate System (MES2-system) [7] are the major models for mesopic

vision.

5

Table 1-1 | Luminous efficiency functions for different usages

Function Luminance Level Field Size CIE Publ. No.

V(λ) Photopic 2° ISO/CIE 10527

VM(λ) Photopic 2° NO. 86 (1990)

V10(λ) Photopic 10° or off fovea beyond 2° ISO/CIE 10527

Vb,p(λ) Photopic Point Source No.75 (1988)

Vb,2(λ) Photopic 2° No.75 (1988)

Vb,10(λ) Photopic 10° or off fovea beyond 2° No.75 (1988)

V‘(λ) Scotopic >2° Proc. 1951

Figure 1-4 | Luminous efficiency functions recognized by CIE [8]

6

Humans with normal color vision have three types of cone receptors and one type of rod receptor

in the eyes. With the combination of three types of cones, people are able to see different colors

in the world. The three types of cones, long-wavelength sensitive (LWS), medium-wavelength

sensitive (MWS), and short-wavelength sensitive (SWS), are often misleadingly called red,

yellow, and green, though they work very much the way of trichromatic theory mentioned below.

These three types of cones have peak sensitivities at 430nm, 530nm, and 560nm. Different

experimental methods get functions slightly different, seen from Figure 1-5.

Figure 1-5 | Normalized cone fundamentals and photopigment sensitivities [8]

1.1.2 Color

Color is an attribute of visual perception that consists of any combination of chromatic and

achromatic content. Different metrics have been defined to describe the attributes of a color.

Spectral power distribution (SPD) describes the power per unit area per unit wavelength of an

illuminant, which is the basis for all the metrics.

Tristimulus Values and Chromaticity Coordinates

7

Trichromatic generalization summarizes the experimental laws of color matching, which states

that many color stimuli can be completely visually matched in color by mixing three fixed

primary stimuli with suitable radiant powers. A system of colorimetry was constructed based on

the principles of trichromacy and Grassmann‘s laws of additive color mixture. Three primary

stimuli were defined which can be mixed to get other colors and none of which can be color

matched by a mixture of the other two. In 1931, CIE adopted the 2º Standard Colorimetric

Observer, characterized by 𝑟 (𝜆), 𝑔 (𝜆), and 𝑏 (𝜆) Color Matching Functions (CMFs) (Figure 1-6),

which allows to represent a color by three tristimlus values. However, sometimes one of the three

primary stimuli have to be added to the test stimulus to match the mixture of the other two

primary stimuli, which will make this stimulus have negative value. A transformation from 𝑟 (𝜆),

𝑔 (𝜆), and 𝑏 (𝜆) to 𝑥 (𝜆), 𝑦 (𝜆), and 𝑧 (𝜆) (Figure 1-7) was established to guarantee the tristimulus

values X, Y, and Z are larger than zero. The sum of the percentage values of the three tristimulus

values is 1.0, thus the percentage values of the first two tristimulus values make up the

chromaticity coordinate, which can be plotted in the CIE 1931 chromaticity diagram. Sometimes,

two stimuli with different SPDs may have the same tristimulus values and chromaticity

coordinates, and they are visually indistinguishable, which is called metamerism.

Like the luminous efficiency function, CMFs were collected based on a 2º field of view. In 1964,

the CIE 10º Standard Colorimetric Observer was established (Figure 1-6, Figure 1-7).

8

Figure 1-6 | RGB color matching functions [8]

Figure 1-7 | XYZ color matching functions [8]

Color Temperature & Correlated Color Temperature

Color temperature is applied to highly selective radiators. When the light of a radiator has the

same or nearly the same chromaticity coordinate as a blackbody radiator at a certain temperature,

this temperature is called the color temperature of the selective radiator.

9

Correlated color temperature (CCT) is introduced when the chromaticity coordinate of a radiator

is not exactly the same as any of the chromaticity coordinate of the blackbody radiator. CCT is

defined as the temperature of the blackbody radiator whose perceived color is most like that of

the given radiator at the same brightness under specific viewing conditions. Figure 1-8 shows the

isotemperature lines calculated by Kelly [9].

Color Rendition

Color rendering ability of a light source is the effect the source has on the color appearance of

objects in comparison with their appearance under a reference source. Though different methods

have been established to evaluate a light source‘s color rendering ability, the most commonly

used method to assess color rendering by a single number is the CIE Color-Rendering Index

(CRI).

Figure 1-8 | The CIE 1976 USC with isotemperature lines

10

CRI is based on the average length of chromaticity-difference shifts between a test light source

and reference light source in the 1964 CIE UCS, which has a maximum value of 100 and

minimum value of zero. A set of eight test-color samples is used to compute CRI, and another set

of six test-color samples is used to compute special CRI. Light sources that render the eight test-

color samples close to the reference illuminant have smaller shifts and higher CRI. Conversely, a

lamp having lower CRI has large color shift for the eight test-color samples compared to the

reference illuminant. The reference illuminant is defined to have the same CCT of the testing

light source. For a lamp with CCT of 5000K or above, the CIE daylight model is used; while for

the lamp with CCT lower than 5000K, a blackbody radiator is used.

However, CRI has some limitations. It uses a single number derived from the color shifts of eight

color samples in the CIE 1964 UCS to describe the color rendering ability. None of these color

samples is highly saturated and the CIE 1964 UCS is non-uniform. Different reference

illuminants are used to calculate CRI for the lamps with different CCT, which does not allow

comparisons between different light sources. In addition, the reference illuminants are not always

ideal for color rendition, though they are defined to have 100 for CRI. With the development of

the light-emitting diode (LED), CRI has been shown to be a poor index to characterize narrow

band spectra [10]. Sometimes, R9 is used to characterize the rendering ability of a source for a

stronger red test color, since red-green contrast is considered important for color rendering [11,

12].

Some other indices of color rendition are commonly used, including Flattery Index (Rf) [13],

Color Discrimination Index (CDI) [14], Color Preference Index (CPI) [15], Gamut Area, FM

Gamut Area, and Color Quality Scale (CQS) [16].

Munsell Color System

11

The Munsell Color System is the most widely used color order system throughout the world. It

specifies color appearance according to three attributes: Hue (H), Value (V), and Chroma (C)

with equal visual increments along each dimension. The definitions of these three attributes

match the definitions of corresponding appearance attributes of hue, lightness, and chroma of

color perception.

Figure 1-9 | Organization of Munsell Color System

The value scale is the anchor of the system with ten main steps. White is given a notation of ten

and black is zero, and intermediate grays are given notations ranging between zero and ten. The

hue circle in the system is divided into five principle hues (purple, blue, green, yellow, and red,

denoted 5P, 5B, 5G, 5Y, and 5R respectively) and is designed to divide the complete hue circle

into equal perceptual intervals. Five intermediate hues are also designated in the system as 5PB,

5BG, 5GY, 5YR, and 5RP for a total of 10 hue names. There are also ten integral hues for each of

the ten hues. For example, for the range between 5PB and 5P, there are 6PB, 7PB, 8PB, 9PB,

12

10PB, 1P, 2P, 3P, and 4P. This type of sequence continues around the entire hue circle, resulting

in 100 integer hue designations that are intended to be equal perceived hue intervals. The third

dimension is chroma. The chroma scale is designed to have equal visual increments from a

chroma of zero for neutral samples to increasing chromas for samples with stronger hue content.

There is no maximum value for the chroma scale. The highest chroma achieved depends on the

hue and value of the samples and the colorants used to produce it.

1.1.3 Theories of Color Vision

The most acceptable theory of color vision today is the product of multiple stages of visual

processing, which originated from Hurvich and Jameson in 1957. This theory is based on the

sequential combination of two prior theories, trichromatic theory and opponent process theory.

Trichromatic Theory

This theory is the first scientific theory of color vision which was initially proposed by George

Palmer, Thomas young, and Helmoholtz [17] individually in the late 1700s. The theory proposed

that there are three primary types of color receptors in the human eyes, nominally red, green, and

blue. All the other colors were explained as combinations of these primaries. These three types of

color receptors respond differently as a function of the wavelength of the light falling on them.

And these three kinds of receptors are regarded to produce peak stimuli in the short-wavelength,

medium-wavelength, and long wavelength region of the spectrum. The theory also explained

some basic phenomena of color vision, such as the three primary colors, the existence of

metamers, and color blindness.

Opponent Process Theory

13

Besides some basic phenomena that can be explained by trichromatic theory, there are still some

other facts that cannot be explained very well. The most striking phenomenon is the experience

that colors are never lost singly, which would be expected based on the trichromatic theory.

Yellow seems to be another primary color as red, green, and blue. In the late 1800s, Ewald

Hering established the opponent process theory, indicating there are four chromatic primaries

rather than three and they are structured into pairs of polar opposites: red-green and blue-yellow.

He agreed with Helmoholtz about three primitive mechanisms but thought there were three

opponent mechanisms instead of the trichromatic primaries. The opponent mechanisms he

believed existed were red-green receptor, yellow-blue receptor, and white-black receptor.

Dual Process Theory

Debates between the two theories above lasted for a long time. Hurvich and Jameson attributed

color vision to both processes. Three photoreceptors are the first step of color vision to perceive

color. The outputs of these three photoreceptors become the input into the opponent channels, as

shown in Figure 1-10. The cells in the retina, bipolar and ganglion cells were also found to

support the dual process theory.

14

Figure 1-10 | A possible diagram of the opponent system

Figure 1-11 | Opponent signals from the possible model of the opponent system (the functions are

linear transformation of CMFs) [8]

15

1.1.4 Changes with Age

The visual system of human beings can be regarded as an image-processing system. The factors

that determine the operating state of the system are the amount of light that reaches the retina and

the wavelengths that the light contains. The factors that determine the clarity of the retinal image

are the ability to focus the image of the external object on the retina, the extent to which light is

forward scattered as it passes through the eye, the presence of stray light produced by back

reflection from the components of the eye, transmittance through the eye wall, and the

fluorescence in the lens of the eye.

As an optical system, the eye has a fixed image distance and a variable object distance. In order to

make the objects with different distances focused onto the retina, the optical power of the eye has

to change, which is determined by the curvature of the cornea and the thickness of the lens. The

curvature of the cornea is fixed, while the thickness of the lens is variable. As the visual system

ages, the range of object distances that can be focused onto the retina decreases because of the

increasing rigidity of the lens. After 60 years old, the eye is virtually a fixed focus optical system.

The optical factors determining the amount of light reaching the retina are the pupil size and the

spectral absorption of the components of the eye. The area of the pupil varies as the amount of

light available changes. The pupil becomes larger to admit more light when there is little, while

the pupil becomes smaller when there is plenty of light. As a person ages, the ratio of the

maximum to the minimum pupil area decreases. The maximum decreases much more than the

minimum does, which means that old people are much less able to compensate for low light

levels by opening the pupils than young people.

16

Figure 1-12 | The Change of pupil diameter with age [1]

As the lens ages, its color changes from clear to yellow and finally brown. With the change of

color, the absorption is also changing. For the spectral absorption of the eye, the majority of the

absorption takes place on passage through the lens. As shown in Figure 1-13, the absorbance of

the lens increases exponentially from birth. The reduction of the optical radiation is not uniform

across the entire spectrum. When people are in their 80‘s or 90‘s, the transmittance of the short-

wavelengths is 10% compared to that at ten years old. Lundeman and his colleague studied the

transmittance of human eyes in donor lenses from the age of 17 to 76 years old. Figure 1-14

shows a significant decrease in transmission in the 400-500 nm range, while in the range of red

color, it only drops slightly [18].

17

Figure 1-13 | The change of absorbance of lens with age [1]

Figure 1-14 | The transmission of the human donor lenses with age [18]

18

A cataract is a clinical term used for a lens which is no longer transparent to light and it is treated

by removing the contents of the lens capsule and replacing the lens by an intraocular lens, called

cataract surgery.

1.2 Objective

In order to evaluate the attributes of light sources, many metrics have been developed in the last

several decades, such as efficacy, CRI, Gamut Area, CCT, and lumen-output. The properties of

lamps are generally indicated using these traditional measurement systems.

Recently, General Electric (GE) Lighting has developed a new family of lamps with non-standard

spectral power distribution, which appears to have better properties than what is indicated by the

traditional metrics. This new family is known as Reveal® and it is commercially available. The

SPDs of the lamps in this family are diminished in the yellow region, as shown in Figure 1-15.

Figure 1-15 | Spectral power distribution of the SPX3K and the RevLF, adjusted so that peak relative

output is at 100%

0%

20%

40%

60%

80%

100%

120%

350 450 550 650 750

Re

lati

ve O

utp

ut

Wavelength (nm)

SPX3K

RevLF

19

This study attempts to draw statistically sound conclusions regarding the differences between a

SPX 3000K Linear Fluorescent Lamp (SPX3K) that has the typical tri-band spectral power

distribution and a Reveal® Linear Fluorescent Lamp (RevLF) that has a diminished yellow

emission spectral power distribution.

Based on the traditional metrics, the SPX3K performs much better than the RevLF does. It has

better color rendition ability and is more efficient.

Table 1-2 | Properties of the SPX3K and the RevLF in GE Catalog

[19]

Power (W) CCT (K) Initial Lumen (lm) Mean Lumen (lm) CRI

SPX3K 32 3000 2950 2800 86

RevLF 32 2600 2475 2225 60

1.3 General Approach

The approach taken was to develop two side-by-side full-scale rooms that permitted the human

subjects to make brightness comparisons and conduct a color discrimination task. Details of the

experimental room are provided in Chapter 3 Design of the Study and Methodology. The

lighting fixtures in the room were specifically designed so that the rooms were indirectly

illuminated. The human subjects were not able to see the light sources directly and the luminance

distributions of the rooms were designed as close as possible when using different lamps.

20

Chapter 2 Literature Review

2.1 Lamp SPD Vs. Spatial Brightness

Brightness is an attribute of a visual sensation in which a stimulus appears to be radiating or

reflecting light. A draft definition of spatial brightness has been proposed by the Illuminating

Engineering Society (IES) Visual Effects of Lamp Spectral Distribution Committee: ―Spatial

brightness describes a visual sensation to the magnitude of the ambient lighting within an

environment, such as a room or lighted street.‖

Numerous studies have been carried out to investigate the relationship between SPD and

brightness perception, which provides some opportunities to reduce illuminance while

maintaining the same brightness perception. Spaces with the same illuminance level appear

differently bright because of the definition of the illuminance. Illuminance is defined based on

𝑉(𝜆), the CIE Standard Photopic Observer, which is different from the visual process of the

brightness perception. The visual system of a human being has three channels: one achromatic

channel and two chromatic channels, which have inputs from different combinations of three

types of cones [20]. 𝑉(𝜆), the CIE Standard Photopic Observer, was collected by flicker

photometry and step-by-step brightness matching which tend to minimize the activities of two

chromatic channels and only take the activity of the achromatic channel into account [3].

However, brightness perception is dependent on the activities of all three channels [21]. Though

the limitations of 𝑉(𝜆) in predicting brightness perception are known [22], including field size,

luminance levels, experimental conditions, and the additivity assumptions, it is still the most

widely used basis to model the quantities in illuminating engineering.

The relationships between brightness and the attributes of color stimuli, such as CCT, CRI,

chromaticity coordinate, saturation, and hue, have been studied by many researchers.

21

Figure 2-1 | Chromaticity diagram of the locations of ten lamps and the average B/L ratios [23]

Correlated Color Temperature (CCT) & Color-Rendering Index (CRI)

Harrington investigated the Brightness/Luminance ratio (B/L ratio) by using color stimuli with

different CCTs ranging from 5380K to 6260K with all having chromaticity coordinates on the

blackbody locus. He found that luminance was required to increase to maintain the same

brightness when CCT decreased, and age had an impact on brightness perception [24]. Alman

used highly saturated colors to run side-by-side matching experiments. He found that B/L ratio

increased with the hue series yellow, orange, green, blue, and red [23]. However, Ayama ran the

experiments on four observers and got an average value of B/L ratios [25] which contradicted the

results drawn by Alman.

22

Alman also found the trend for the colors close to the blackbody locus [23]. For colors with CCT

above 3000K, B/L ratio increased when CCT increased, while for the color with CCTs lower than

3000K, B/L ratio increased when CCT decreased, shown as Figure 2-2. Using semantic rating

scales to compare side-by-side booths, Delaney found approximately equal ratings of brightness

for lamps with CCT of 5000K and 4200K, but progressively better ratings for the lamps with

higher CCT as the difference in CCT increased [26]. Boyce and Cuttle compared four fluorescent

lamps with CCT of 2700K, 3500K, 4200K, and 6300K, with CRI in the range of 82-85. A 5-point

rating scale was employed in the experiment. They found that in achromatic rooms, CCT did not

affect the ratings of brightness and glare, while in colored rooms, rooms with 6300K were rated

less bright than the rooms with 2700K or 3500K [27]. Hu and her colleagues ran side-by-side

comparisons of brightness perception and side-by-side dimming adjustments for brightness

matching, showing that CCT and brightness perception were not related [28].

23

Figure 2-2 | B/L ratio contours on the 1931CIE chromaticity diagram [25]

Figure 2-3 | Section of the CIE 1931 chromaticity diagram including 16 lamps whose chromaticity

coordinates were close to the blackbody locus and B/L ratio versus CCT [23]

24

Figure 2-4 | Relationship between brightness and CCT. (a) Percentage of subjects selecting 3500K

lamps over 6500K lamps in side-by-side comparisons; (b) Mean adjusted illuminance and standard

deviations for two pairs of comparisons in the brightness matching trials [28]

CRI is regarded as another method to describe the attribute of a light source. Fotios summarized

the comparison between two lamps, A and B. If lamp A had a higher CCT and CRI than lamp B

does, the interior appeared brighter when using lamp A. If the lamps had similar CCTs, the

interior appears brighter when using the lamp with higher CRI. He also suggested that

consideration of CRI and CCT together provide a better prediction of color appearance. Lamps

with higher CRI and CCT would be perceived brighter, and could be set to a lower illuminance

level for equal perceived brightness [29].

All the studies above investigated the relationship between CCT, CRI, chromaticity coordinates,

and brightness perception. Most of the experiments were carried out for small viewing fields,

which is the same limitation of 𝑉(𝜆). They used different lamps to illuminate chips for observing

and evaluating brightness. However, the materials, and reflectance of the chip could be the factors

25

that affect the sensation of the observers. For architectural engineering and interior lighting,

perception mainly focuses on large viewing fields. All the conclusions made above should be

reconsidered if applied to a large viewing field. In short, none of CCT, CRI, Gamut Area, and

chromaticity coordinates alone would be able to predict the brightness response, which was

concluded by Fotios [29].

Prime Color Theory

In 1777, George Palmer found that there were three types of color receptors in a human‘s eyes,

which produce the primary color sensations. Thornton studied the trichromatic response from

several points-of-view, including brightness perception [30] and color preference. He called the

regions near 450nm, 530nm, and 610nm in spectrum the ―prime colors‖, which were able to

enhance both brightness and color perception. In contrast, the intermediate regions around 500nm

and 580nm were called the ―anti-prime colors‖, which can worsen brightness and color

perception. That is the basis for tri-phosphor fluorescent lamps.

Thornton concluded that the three most effective wavelengths in white light were near 450nm,

540nm, and 610nm for CRI. Conversely, composition of white light should avoid wavelengths

near 500nm and 580nm, which were ineffective. Elimination of wavelengths near 500nm or

580nm improved the CRI and color discrimination significantly [31, 32]. In the 1990s, a series of

experiments of perceived brightness were carried out by Thornton. Three primary colors were

used to match the broadband-white fluorescent lamps in brightness by the Maxwell Method:

452nm-533nm-607nm, 477nm-558nm-638nm, and 497nm-579nm-653nm. Two spectral lights

were held at primary wavelengths, while the third was varied through the remaining primary. He

found that the least power was required for brightness matching near 450nm, 530nm, and 610nm,

while the most power was required near 500nm or 570nm, which was independent both of

26

primaries and of colorimetric assumption [33]. Another experiment method, the Maximum

Saturation Method, was also used. A spectral light of variable wavelength was mixed with one of

the primary to match the other two primaries. The same three primaries sets were used [33].

Figure 2-5 | Ratio of power of lights to total power (Left: ratio of the power of light at variable

wavelength to total power. Right: ratio of the power of two primary lights to total power) Red lines

indicate the wavelengths require less power, and blue lines indicate the wavelengths require more

power [33]

Houser and his colleagues ran a pilot study based on Thornton‘s prime color theory. By

increasing the magnitude of radiation within the prime-color regions, brightness and color

preference were found to increase, which supported the prime color theory. A conclusion was

drawn that the perception of brightness and visual clarity depend on the placement of radiant

power within key spectral regions. More energy within the 450nm-530nm-610nm regions led to

enhanced brightness perception and color preference [34].

Opponent Process

Based on the theory of dual process of the visual system, some theories about brightness were

established based on the opponent system. Several simple linear models were established. The

27

brightness meter invented by Thornton was expressed as 𝛽 = 𝐿 + 𝐵 − 𝑌 + 𝐺 − 𝑅 [35]. The

brightness model established by Thornton was expressed as 𝛽 = 𝑌 + 𝑀 + 𝑁 [30]. And the

vector luminance model of Guth and Lodge was given by 𝐿 = 𝐴2 + 𝑇2 + 𝐷2 1/2 [36]. The

luminance model and brightness model were based on the chromatic and achromatic channels

from the transformation of the CIE 1931 Standard Colorimetric Observer. The perceived

brightness was the sum of the activities in three channels, but the summation is confused by the

arbitrary signs of the red-green and blue-yellow channels. Thus, Guth and Lodge used a vector

sum in the vector luminance model and Thornton summed the absolute values in the three

channels in his brightness model. The brightness meter established by Thornton was found to be

the most accurate among the three. Some other models were developed by Fotios [37-39],

Yaguchi [40], Nayatani [41], Fairchild [42], and Houser [22]. All of these models provide better

prediction of brightness than 𝑉(𝜆) does, though they are still not perfect [43].

S/P Ratio or C/P Ratio

Berman argued that rods contribute to the spatial brightness for large fields of view at photopic

vision. He thought the perception of spatial brightness is related to the ratio of scotopic to

photopic lumens (S/P ratio), suggesting that at equal luminance, lamps with a higher proportion

of energy in short-wavelength regions will be perceived brighter [44]. Based on psychophysical

experiments, he found differences in brightness between stimuli with the same chromaticity

coordinates and photopic luminance. He argued that the same chromaticity coordinates and

photopic luminance should provide equal excitation to the cone receptors, so the differences of

the brightness perception cannot solely be due to cone receptors. Rods must be active at these

light levels [44]. He promoted P(S/P)0.5 as a correlate for brightness perception and stating that

the lamps with a high S/P ratio should be promoted as a method for reducing energy

28

consumption. Berman also supported that the cirtopic spectral sensitivity is the true driver of the

brightness perception while scotopic sensitivity can explain the effect because the scotopic and

cirtopic functions have peaks near to each other [45]. The other reason to use C/P ratio is it

correlates with the change in pupil size driven by the intrinsically photosensitive Retinal

Ganglion Cell (ipRGC).

However, rod response is generally considered to be saturated at photopic levels, which means

rods should make little contribution to brightness perception. The response of SWS is considered

alternatively in the S/P ratio. Stockman [46] and Ingling [47] found the contribution of SWS to

brightness perception. A model of P(SWS/P)0.24 was proposed by Fotios to predict brightness

perception [39]. It was also mentioned by Berman that this relationship might not be accurate for

narrow band sources such as LEDs.

Houser and his colleagues ran experiments to test brightness perception. The stimuli of two S/P

ratios were applied in the experiment. Both of them were on the blackbody locus. Two luminance

levels were used. The conclusion from the experiments indicated that S/P ratio and CCT were not

able to predict brightness perception, at least for the stimuli on the blackbody locus, though the

stimuli in this experiment were not representative of light stimuli [48].

2.2 Experimental Methods for Brightness Perception

Over 60 studies have been carried out to investigate the relationship between SPD and spatial

brightness perception. Different experiments were designed and provided the different

conclusions. Some of them reported a significant effect of SPD, while others concluded little

effect. Experimental procedures should be designed carefully to get reliable results.

29

Joint and separate evaluations are the two major methods of evaluation. In separate evaluation,

stimuli are presented individually, while in joint evaluation, two or more stimuli are presented at

the same time. The joint evaluation method can be subdivided into simultaneous and sequential

modes. Simultaneous mode means the stimuli are presented side-by-side, while the sequential

mode means the stimuli are presented in temporal juxtaposition.

Rating, ranking, and matching are the three possible responses provided from the subjects. Rating

is the method that requires subjects to rate the level of brightness of a space. Providing a standard

for this rating is required to get reliable results. Ranking method requires the subjects to rank the

stimuli from brightest to darkest. Matching requires the subjects to dim one stimulus to match the

brightness of the other stimulus. Fotios provided a very good summary of the methods required

for reliable studies in Table 2-1 [49].

Table 2-1 | Studies giving reliable results of SPD effect on brightness [49]

Study Response Field Size Evaluation Mode

Akashi & Boyce [50] Yes/No Response to Statements Full Field Separate

Berman et al. [51] Forced Choice Full Field Sequential

Boyce [52] Matching Full Field Simultaneous

Boyce et al. [53] Yes/No Response to Statements Full Field Separate

Boyce and Cuttle [54] Rating Full Field Separate

Flynn and Spencer [55] Rating Full Field Separate

Fotios and Gado [56] Matching 40º high, 72º wide Simultaneous

Fotios and Levermore [57] Matching 22º high, 38º wide Simultaneous

Houser et al. [34] Forced Choice Full Field Simultaneous

Houser et al. [48] Forced Choice Full Field Simultaneous

Houser et al. [48] Forced Choice Full Field Sequential

30

Hu et al. [28] Matching Full Field Simultaneous

Thornton and Chen [58] Matching 30º high, 50º wide Simultaneous

Vrabel et al. [59] Forced Choice Full Field Sequential

Vrabel et al. [59] Rating Full Field Separate

Only 13 out of 60 previous studies seem to be reliable. The aspects of these procedures were

counterbalanced or randomized, null condition trials were included, and clear statistical analysis

was used in these studies. Counterbalanced or randomized procedures were used to guarantee that

there was no order or positional bias in the results.

Chromatic adaptation should be considered in the experiment. In simultaneous mode, subjects

adapt to a mixed spectrum where the white point is somewhere between the two stimuli. In rapid-

sequential mode, the duration of the stimuli need to be controlled within 3-5 seconds, at which

point the chromatic adaptation tends to be only about 60% complete.

When using side-by-side ranking tests, the frequency of stimuli may introduce bias. When a

forced-choice is required between reference illuminant and test illuminant, the subject may not

compare the test lights to the reference, but instead to the overall range of test lights, which

means the middle of the range presented will be the one found to be equally bright as the

reference [60].

2.3 Color Discrimination

Color rendering consists of three components, which may not be correlated well with each other.

The three components include the accurate rendition of colors or colors of objects as they appear

31

under the reference light source, the rendition of colors that make objects appear more pleasing

(vivid or flattering), and the capability of a lamp to allow for human beings to distinguish

between a large variety of colors when viewed simultaneously. These are noted as fidelity,

appeal, and discrimination [8]. Different metrics have been established for these. CRI is an index

to qualify the fidelity. FI [13] and CPI [15] measure the appeal of a lamp. CDI [14] and Gamut

Area Index (GAI) [61] provide a measurement of color discrimination. Jerome concluded that

maximizing one element might be detrimental to another [62].

Both CDI and GAI are calculating the area enclosed by the eight test-color samples used in CRI

in the CIE 1960 UCS. The difference between them is the scaling method to calculate the index.

The number of test color samples and the uniformity of UCS are the two limitations of CDI and

GAI. FM Gamut calculates the gamut area enclosed by the 85 color samples of Farnsworth-

Munsell 100 Hue Test (FM-100) in the CIE 1960 UCS, which is a similar method to CDI. Royer

and his colleague failed to find a good predictor among CRI, CDI and FM Gamut Area for color

discrimination [63]. Thus, it is not beneficial to use an index to predict the color discrimination

ability of a light source or a spectrum.

FM-100 was designed by Farnsworth in 1943 [64], which is widely used in color vision tests.

Many studies have been conducted to investigate the effects of SPD, illuminance level, age, and

color deficiency on the color discrimination by using FM-100.

In 1976, Boyce ran an experiment to see the impact of illuminance level on color discrimination.

Fifteen subjects performed the FM-100 under four different fluorescent lamps and two different

illuminance levels. Boyce drew the conclusion that the illuminance levels within 300-1000 lux

had no impact on color discrimination [65]. A study in 1977 carried out by Boyce included more

light sources showed the same results [66]. Bowman reviewed all the literature in 1980 and

32

carried an experiment with 10 subjects. He drew the conclusion that the Total Error Score (TES)

of FM-100 increased when the illuminance level decreased. When the illuminance level was

above 100 lux, the improvement of color discrimination was not statistically significant [67].

Figure 2-6 summarizes the results of TES of FM-100 versus illuminance level.

Figure 2-6 | Total Error Score (TES) of FM-100 versus the illuminance level for different age groups

[67]

For the relationship between stimulus and color discrimination performance of FM-100, Boyce

found that light sources with higher CRI improved color discrimination performance [65, 66].

And it was similar for CIE Gamut Area and CDI [66]. For the lamps with similar CRI, it was

found that higher CCT led to a reduction in TES [54]. However, no significant difference was

found among a 2900K halogen lamp, 3000K tri-band CFL, and 5000K full spectrum CFL [68].

Age is another factor that is thought to affect color discrimination performance. It has been

generally accepted that older people consistently produced much worse performance than

33

younger people and middle-aged people [66, 68, 69]. When changing light settings during

experiments, longer adaptation time was needed by the older subjects [68].

Figure 2-7 | Color discrimination performance of FM-100 for each age group and illuminance level

[69]

2.4 Spectral Modification

Many studies tried to modify SPD to improve visual performance for people.

Using goggles or contacts were the most widely used methods for spectral modification. In 1983,

Kinney compared the visual performance of subjects between yellow goggles and neutral goggles

34

with equal transmittance. Subjects wearing yellow goggles showed faster reaction time [70].

However, both of the chromatic channels, yellow-blue and red-green, were affected in the same

direction by yellow cutoff filters, so the relative contribution to the results was unknown. In 1990,

a similar experiment was carried out by Kelly to investigate the impact of yellow goggles on

brightness perception. He found that brightness perception was enhanced about 40% by yellow

goggles when the spatial extent of the stimulus exceeded to fovea [71], which also supported the

failure of S/P in predicting brightness.

Figure 2-8 | Transmittance of the lens used for spectral modification [71]

X-Chorm lens, a broadband red contact lens, is another way to modify the spectrum entering

people‘s eyes. In some instances, significant improvements in color discrimination have been

reported for color-deficient observers by using X-Chrom lens, whereas other investigations have

found minimal or no beneficial effects. Matsumoto summarized that these discrepancies may in

part be due to the different color tests that have been used to assess vision [72]. In general,

35

improvements in performance have been reported for evaluations performed with

pseudoisochromatic plates. Other tests, including FM-100, Farnsworth D-15, have shown

minimal or no effects of X-Chrom lens.

36

Chapter 3 Design of the Study and Methodology

3.1 Apparatus

The experiments were carried out in Penn State‘s Lighting Lab in University Park, PA. Two

rooms enclosed on three sides, with nominal dimensions of 10 feet (width) × 12 feet (depth) × 9

feet (height), were built adjacent to each other. The walls were painted with Munsell N8

spectrally neutral paint. The rooms were enclosed with a black felt curtain behind the subject and

out of his or her field of view. 2 feet × 2 feet acoustical tiles were used for the ceiling and gray

carpeting was placed on the floor. Four 8-foot indirect pendant luminaires were installed in each

room, suspended 15 inches below the ceiling. Baffles made of white foam core were placed on

the luminaires to prevent subjects from seeing lamps directly (Note: the baffles were not needed

to shield a direct view of the linear fluorescent lamps, but were needed to shield the view of

screw-based LED lamps that were also mounted in the luminaire. The LED lamps are for a

related study, but not reported here). Two RevLF and two SPX3K lamps were installed in each

luminaire, which were connected to Lutron Hi-lume 3D ballasts. Figure 3-1 shows the installation

of the lamps, luminaires, and baffles. The lamps in the luminaires in each room were mirrored

(i.e. SPX3K lamps were installed on the left side on each luminaire in the left room and on the

room side on each luminaire in the right room). Lutron Grafik Eye® QS interfaces were used to

control the lamps, with one control system for each room. The physical properties of the two

rooms were as near to each other as possible so that we could isolate SPD as the only variable.

37

Figure 3-1 | Photograph of the installation of the lamps, luminaires and baffles

For the session on perceived brightness, a table was positioned against the dividing wall, such

that when the subject was seated his or her sagittal plane aligned with the middle of the two

spaces. The subject was seated with his or her head positioned in a chin and forehead rest. Eye

height was approximately 46.5 inch above the floor, varying slightly with the size of a subject‘s

head, which was computed based on the 95th percentiles of the static dimensions of the U.S.

civilian population [73]. The subject was instructed that he or she was free to rotate his or her

head within the rest, but to focus on the back walls of the rooms when making judgments. A view

from behind the subject‘s seated position is shown in Figure 3-2.

38

Figure 3-2 | A view from behind the subject’s seated position in the session on perceived brightness

For the session on color discrimination, a table with neutral grey top was placed in the center of

the room 9 feet from the back wall. The height of the table was 2.5 feet above the floor, where the

subject performed the color discrimination task. The subject was free to move and adjust the

height of the chair to sit comfortably. The color discrimination task was presented in the center of

the table to match the place where calibration measurements were taken. All of the color

discrimination experiments were carried out in the right room. A view from behind the subject‘s

seated position is shown in Figure 3-3.

39

Figure 3-3 | A view from behind the subject’s seated position in the session on color discrimination

3.2 Subjects

60 subjects were recruited, 30 in each age group. The younger group was 25 years or younger and

the older group was 60 years old or greater.

All subjects in the younger group were recruited via an email distribution list that includes

students at the University Park campus of Penn State University. Most of them were students in

Architectural Engineering. All of them were studying disciplines other than lighting. All subjects

in the older group were recruited from the residents of The Village at Penn State, a retirement

community in State College, PA. They were recruited with a flyer sent to the front desk of The

Village at Penn State. Interested residents selected an available time-slot and signed-up with the

receptionist. There were no criteria to exclude participants except age. Each subject was paid $75.

40

The recruitment materials and experimental procedures were approved by Penn State‘s

Institutional Review Board (IRB #35919). Each subject was assigned a randomly generated four-

digit ID to maintain confidentiality.

Table 3-1 summarizes demographic data for the subjects, including the mean age, age range,

gender, number of subjects with cataract surgery, and number of subjects with abnormal vision.

None of the subjects had knowledge about the lamps that were used in the experiment.

Table 3-1 | Demographic summary of the subjects. (Of the 3 subjects in the older group with

abnormal color vision, all of them had had cataract surgery)

Age Group

Number

of

Subjects

Average

Age

(Range)

Std.

Dev Gender

Number of

Subjects with

Cataract

Surgery

Number of

Subjects with

Abnormal Color

Vision

Younger (≤ 25 years of

age) 30 22.3

(19-24) 1.70 19 Males 11 Females 0 1

Older (≥60 years of

age) 30 81.4

(61-92) 7.09 11 Males 19 Females 20 3

3.3 Independent Variables

3.3.1 Independent Variables for Perceived Brightness

For the session on perceived brightness, the independent variables were age group, spectral power

distribution (SPD), and illuminance.

The RevLF and the SPX3K were employed to provide two different SPDs. A StellarNet

EPP2000c spectrometer was used to measure the SPDs, from 380 nm to 780 nm with 5 nm

increments. The remote integrating sphere was positioned on the table where the subject was

41

seated for the session on perceived brightness. The opening of the integrating sphere was oriented

up. The SPDs used in analysis were derived from the average of the measurements taken at

different times during the course of the experiment with one light setting in either room, which

provided a best description of the stimuli viewed by the subjects. Figure 3-4 shows the average

SPDs measured by the spectrometer and Table 3-2 is the summary of the characteristics of the

two SPDs.

Figure 3-4 | The SPDs of the two stimuli – the SPX3K and the RevLF - each an average of

measurements

0%

20%

40%

60%

80%

100%

120%

350 450 550 650 750

Re

lati

ve O

utp

ut

Wavelength (nm)

SPX3K

RevLF

42

Table 3-2 | Characterization of the average SPDs for the SPX3K and the RevLF

SPD CCT (K) CRI

1931 CIE 2°

chromaticity

coordinates

(x, y)

1976 CIE 2°

chromaticity

coordinates

(u’, v’)

SPX3K 2858 86 (0.436, 0.387) (0.258, 0.513)

RevLF 2577 61 (0.449, 0.377) (0.273, 0.512)

Illuminance levels for the perceived brightness sessions were selected to find the illuminance

ratio of RevLF to SPX3K, at which the rooms were perceived as equally bright. The Lutron

Grafik Eye® QS system was employed to dim the fluorescent lamps. Four scenes with

illuminance levels of 240 lux, 270 lux, 300 lux, and 330 lux, were programmed for the SPX3K.

At each of these four illuminance levels for the SPX3K, four scenes were programmed for the

RevLF, with percent of the SPX3K illuminance corresponding to 80%, 90%, 100%, and 110%, as

shown in Table 3-3. The reason for selecting these ratios is discussed in 3.5.1 Statistical Design

for Perceived Brightness. All illuminance levels are typical for interior spaces under photopic

vision. In all, there were ten different illuminance levels (each corresponding to a ‗scene‘, or

‗light setting‘) for the RevLF since some scenes could be reused for different levels of the

SPX3K. For example, 330 lux was one scene for the RevLF, which is both 110% of 300 lux and

100% of 300 lux. Totally, 14 different scenes were designed for the session on perceived

brightness, as summarized in

Table 3-4. A series pairs of light settings were presented to each subject to judge in the session on

perceived brightness, as described in 3.5.1 Statistical Design for Perceived Brightness.

43

Table 3-3 | Horizontal illuminance programmed for the SPX3K and the RevLF

Horizontal Illuminance of the

SPX3K (lux)

Horizontal Illuminance of the RevLF at different

illuminance ratios (lux)

80% 90% 100% 110%

240 192 216 240 264

270 216 243 270 297

300 240 270 300 330

330 264 297 330 363

Table 3-4 | Summary information of light settings and nominal calibration characteristics. Both

rooms required and identical set of light setting, for a total of 28 light settings, each corresponding to

a scene programmed into one of the two Lutron Grafik Eye® controllers

No. of Setting SPD Horizontal Illuminance (lux)

1 SPX3K 240

2 SPX3K 270

3 SPX3K 300

4 SPX3K 330

5 RevLF 192

6 RevLF 216

7 RevLF 240

8 RevLF 243

9 RevLF 264

10 RevLF 270

11 RevLF 297

12 RevLF 300

13 RevLF 330

14 RevLF 363

44

Each light setting was separately calibrated—in each room—to be as close to the target

illuminance as possible. On each experiment day, all lamps were turned on more than one hour

before arrival of the first subject. Before running the first subject and after the last subject of the

day, two Minolta T-10 illuminance meters were used to measure the illuminance in each room

and to verify the calibration settings. Both meters were calibrated immediately prior to this study

and NIST traceable calibration certificates are on file. The calibration and measurement

procedures were identical for both rooms. Within one of the rooms, one meter was oriented up

and positioned on a tripod centered in the room with the photocell 2.5 feet above the floor and 9

feet from the back wall, corresponding to where the subject performed the color discrimination

task. The other meter was positioned on a tripod 6 feet from the back wall, oriented vertically,

and aligned with a point 46.5 inch above the floor in the center of the back wall of the room, since

this corresponded to the viewing plane that each subject was asked to focus on when making

brightness judgments. Figure 3-5 is a photograph taken during calibration. The horizontal

illuminance measurements were used for calibration; the vertical measurements were taken to

verify the similarity of the luminance distribution in the two rooms. Table 3-5 shows the mean

and standard deviation for each of the 14 light settings in both rooms, summarizing the horizontal

and vertical illuminance measurements.

45

Figure 3-5 | Photograph of the calibration during the course of the experiment

Table 3-5 | Average and standard deviation of the illuminance of the light settings measured in each

room

No. of

Setting

Left Room Illuminance (lux) Right Room Illuminance (lux)

Horizontal Vertical Horizontal Vertical

Ave St. Dev. Ave St. Dev. Ave St. Dev. Ave St. Dev.

1 243.2 1.4 141.3 1.0 245.3 1.3 143.0 1.0

2 269.4 1.3 156.6 0.9 272.7 1.4 158.9 1.0

3 297.3 2.0 172.8 1.3 301.3 1.1 175.9 1.1

4 331.4 1.3 192.7 1.1 328.0 1.3 191.8 1.0

5 195.7 0.9 114.1 0.8 195.6 2.0 113.2 1.3

6 220.1 0.8 128.1 0.7 222.7 2.8 129.4 1.1

7 243.7 0.9 141.8 0.9 248.9 2.0 144.0 1.3

8 243.8 1.0 141.9 1.0 249.3 2.0 144.2 1.3

9 260.7 0.8 152.1 1.0 258.6 1.7 149.5 0.9

10 269.9 1.8 157.2 0.9 268.5 1.5 155.2 0.7

11 292.9 1.0 170.7 1.0 295.6 1.2 171.0 0.9

12 305.7 1.3 178.2 1.0 309.3 1.4 178.9 0.8

13 332.2 1.3 193.6 1.0 335.4 1.4 194.2 0.8

46

14 358.5 1.4 208.8 1.3 362.2 2.0 209.8 1.1

As mentioned above, SPDs were also measured at different times during the course of the

experiment. All chromaticity coordinates, which were computed from the SPDs, are enclosed by

a four-step MacAdam Ellipse, as shown in Figure 3-6 . Thus, the stimuli in each room were

similar to the other over the duration of the study; all subjects experienced comparable

conditions.

Figure 3-6 | Chromaticity coordinates plotted in the 1931 CIE chromaticity diagram for all

measurements. The coordinates for each measurement can be enclosed by a four-step MacAdam

Ellipse. The measurements were taken at different times during the course of the experiment for one

of the light settings in one room each time

0.35

0.36

0.37

0.38

0.39

0.40

0.41

0.42

0.43

0.44

0.45

0.40 0.41 0.42 0.43 0.44 0.45 0.46 0.47 0.48 0.49 0.50

y

x

SPX3K

RevFL

Blackbody Locus

SPX3K Left Room

SPX3K Right Room

RevFL Left Room

RevFL Right Room

47

3.3.2 Independent Variables for Color Discrimination

For the session on color discrimination, age group and SPD were the independent variables with a

fixed horizontal illuminance of 300 lux on the desktop.

300 lux was chosen in part because it is recommended by IES for common visual tasks. It is also

at the low end of the range employed by Boyce and Simons, who found that illuminance did not

affect color discrimination as characterized by the FM-100 test when illuminance was in the

range of 300 to 1200 lux [66]. In addition to the SPX3K and RevLF, a third light setting was

created with Soft White LED lamps.

3.4 Dependent Variables

3.4.1 Dependent Variables for Perceived Brightness

For the perceived brightness sessions, a series of pairs of light settings were presented to a

subject. The subject was instructed to give a forced choice, that is, to judge which light setting of

the pair appeared brighter. If the subject declared that the two stimuli were the same, the

experimenter instructed him or her to make a choice. The choice made by the subject was the

dependent variable for these sessions.

3.4.2 Dependent Variables for Color Discrimination

For the session on color discrimination, each subject completed the Farnsworth Munsell 100 Hue

Test (FM-100) under each light setting. Though the FM-100 was originally created to

characterize defective color vision, it is a suitable task to characterize color discrimination ability;

it covers the complete hue circle, can be easily scored, is readily available, and has a proven track

record. Each subject completed the FM-100 test under a Soft White LED light setting, in addition

to the SPX3K and RevLF light settings, for a total of three tests.

48

The FM-100 consists of 85 color caps, which are presented in four trays. The two end caps of

each tray are fixed, while the rest of the caps are shuffled on the table. The subject is instructed to

arrange the caps in color order for each tray, making a regular color change between the two end

caps. The back of each cap has a number corresponding to the correct order. The arrangement of

the caps is graded by Total Error Score (TES), which is the sum of scores for all the individual

caps. The score for an individual cap is the sum of the differences between the number of that cap

and the numbers of the two adjacent caps minus two. For example, if three caps are arranged as 3-

6-5, the error score for cap 6 would be (6-3)+(6-5)-2=2. Furthermore, TES can be divided into

two Partial Error Scores (PESs), red-green (R-G PES) and blue-yellow (B-Y PES). The R-G PES

is the sum of the error scores of cap 13 to 33 and 55 to 75 and the B-Y PES is the sum of the error

scores of cap 1 to 12, 34 to 54, and 76 to 85. The scores associated with these caps characterize

color discrimination ability for red-green and blue-yellow colors, respectively. The lower the TES

and PES, the better the color discrimination ability. Thus, TES, R-G PES, and B-Y PES were the

three dependent variables for the color discrimination sessions.

3.5 Statistical Design

3.5.1 Statistical Design for Perceived Brightness

In the session on perceived brightness, each illuminance level of the SPX3K was compared with

the four illuminance levels of the RevLF, with RevLF to SPX3K illuminance ratios of 80%, 90%,

100%, and 110%. Subjects always judged pairs of light settings, with SPX3K illumination in one

room and RevLF illumination in the other, or, for the null condition trials, identical illumination

in both rooms.

To determine the illuminance ratio of RevLF to SPX3K where brightness was perceived to be

equal, two regression lines can be computed based on percentages of subject votes for the brighter

49

light setting of a pair. This analysis method is further described in 3.6 Experimental Procedures.

When considering a single paired comparison, it would have been undesirable to have all subjects

vote for the same light setting of the pair all the time. This would occur if the brightness

differences were very obviously different, for example by presenting twice as much illuminance

in one room versus the other. Such data would also be indeterminate because it would skew the

slope of the regression lines and the location of the intersection points. To avoid this situation,

three pilot studies were completed before the main experiment to study different illuminance

ratios and to fix those used in the main study. The increments of the pilot study were RevLF to

SPX3K illuminance ratios of: Pilot 1, 60%, 80%, 100%, 120%; Pilot 2, 70%, 85%, 100%, 115%;

and Pilot Study 3, 80%, 90%, 100%, 110%. A separate analysis, not provided, showed that

nearly 100% of the responses favored the higher illuminance when ratios of 60%, 70%, 115%,

and 120% were employed. In the pilot study where 10% increments (i.e. 80%, 90%, 100%,

110%) were employed, it became more difficult for the subjects to make the judgments, and

different judgments for the same pairs of light setting appeared. These increments were therefore

employed for the full study.

The stimulus frequency bias is a possible bias for side-by-side brightness ranking evaluation

mode. The stimulus frequency refers to the distribution of comparison illuminances above and

below the illuminance at which equal brightness is expected. If the distribution is fairly balanced,

having the same number of illuminances above and below the illuminance for equal brightness,

both stimuli will be selected as brighter on a near equal frequency. However, if the distribution is

not balanced, having unequal number of illuminances above and below the illuminance for equal

brightness, one stimulus will tend to be selected brighter more frequently than the other. And the

subjects would tend to respond as the frequency was balanced, which would suggest a difference

50

between two stimuli when it does not exist [74]. In this study, it was expected that the

illuminance ratio of RevLF to SPX3K was between 90% to 100% for equal brightness, so the

same number of ratios were required to above or equal 100% and below or equal 90%.

In order to counter a possible positional bias associated with the side-by-side method, all pairs of

SPX3K and RevLF light settings were presented in left-right and right-left scenarios, as shown in

Figure 3-7. Thus thirty-two pairs were compared between SPX3K and RevLF for each subject,

with eight for each illuminance level of SPX3K. Another eight null conditional pairs were

presented to each subject comprised of four pairs for SPX3K and four pairs for RevLF. For the

null condition trials, the same light setting was presented in both rooms, as shown in Figure 3-2,

such that the response should be based on chance.

Each session began with four practice trials, in which the subject was free to ask questions and

became familiar with the process. In total, each subject made 44 force choice comparisons (4

practice trials + 32 comparison trials + 8 null condition trials). The practice trials were not

randomized; they were instead purposely selected to present the range of conditions the subject

would experience, including the largest illuminance ratio difference and a null condition trial.

Figure 3-7 | Example of light settings provided for counter-balance

51

3.5.2 Statistical Design for Color Discrimination

In the session on color discrimination, each subject finished three FM-100 tests, with one under

each SPD at 300 lux (Note: subjects also performed the FM-100 test under Soft White LED

illumination. Data for that experiment are not reported here). The order of the SPD was

randomized, and under each SPD, the order of the four trays presented to each subject was also

randomized.

3.6 Experimental Procedures

This study was approved by Penn State‘s Institutional Review Board (IRB #35919). Upon arrival,

subjects read a brief description of the experiment, signed an informed consent form, and filled

out a general information survey which included a question about whether or not they had

cataract surgery. The Keystone Visual Skills Test and the 24 Plate Ishihara Color Vision Test

were administered. One male in the younger group, and two males and one female in older group

had abnormal results in the Ishihara Test.

After vision screening, the light settings in both experimental rooms were switched to the first

experiment condition for color discrimination. Before entering the room, the subject experienced

a washout period of two to three minutes, during which they sat in a windowless room

illuminated to 300 lux by 3000K linear fluorescent lamps. Once the washout period was

complete, the subject was escorted into the right room where he or she sat at the table. After

listening to the instruction read by the experimenter, one of the four FM-100 trays was brought

into the room and the caps were shuffled on the table in front of the subject. The instructions were

always read from a script to minimize the variation between subjects. After the experimenter left

the experimental room, the subject was instructed to start arranging the caps. There was no time

limit for the subject to finish each tray, but he or she was given a notification at two minutes.

52

When the subject indicated that he or she had finished arranging the caps, the next tray was

brought in and the previous was taken to be recorded by the experimenter. The order of the trays

shown to the subject was randomized. After finishing all four trays under the first light setting,

the subject was instructed to step out of the room to complete the three-minute washout period

and the light settings in both rooms were switched to the next light setting. The washout period

also allowed for the stabilization of the lighting system. After the washout period, the subject

returned into the room to perform the next FM-100.

After the session on color discrimination, the table used for FM-100 test was removed. Another

three-minute washout period was required. The subject sat outside the experiment room in a

windowless room illuminated to 300 lux with 3000K linear fluorescent lamps, during which the

lamps in both rooms were set at full output to assist with stabilization. Then the subject was

escorted through the felt curtain and seated at the table, which was set against the diving wall

between two rooms. He or she was instructed to adjust the height of the seat to comfortably place

his or her head in the chin and forehead rest. Next, the experimenter read the instructions and

answered questions raised by the subject. The instructions were always read from a script. After

four practice trials, the recorded trials began. The experimenter advanced the light settings to the

next pair according to a pre-written script. The subject was instructed to close his or her eyes

when the lamps were changed to the next pair. This was so that he or she would not compare the

new setting to what was previously seen, and instead focus only on the side-by-side comparisons.

This also helped to ensure that the lamps were stable when the subject first viewed the pair. After

several seconds the subject was instructed to open his or her eyes, then to simply observe while

holding judgment for at least 30 seconds to allow for adaptation to the new settings. The

experimenter prompted the subject after 30 seconds, but he or she was allowed to take as much

53

time as necessary to judge which room appeared brighter. The subject was instructed to make his

or her judgment only based on brightness rather than color difference. The experimenter recorded

the subject‘s response on a form, before moving to the next pair.

After finishing all 40 pairs, the light settings in both rooms were changed to 330 lux, with RevLF

in one room and SPX3K in the other. After 30 seconds, the subject was instructed to stand up and

walk into the rooms. He or she was free to walk back and forth and look around between both

rooms and to judge which room he or she preferred. Specific evaluation criteria were not given to

the subject. The experimenter recorded the subject‘s response and also the reason for the

preference, as explained by the subject. There was no time limit for the subject to make this

judgment or to share observations with the experimenter. The entire procedure took between 1.5

and 2 hours.

54

Chapter 4 Analysis and Results

4.1 Data Reliability: Null Condition Trials and Tests for Bias

As shown in Table 3-5, the average horizontal and vertical illuminance in the left room and right

room were not identical. Across all light settings, the mean horizontal and vertical illuminance in

the left room were 2.07 lux and 0.63 lux lower than the right room at the calibration point. By

presenting all pairs of light settings in both rooms, the effect of the difference was distributed

evenly across all stimuli. Null condition trials were included to establish the prevalence of bias.

The results of these tests are shown in Table 4-1. Overall, the subjects chose the left room 48

percent of the time in the null condition trials. None of the null condition trials had bias, with the

p-value for the Chi-Square Goodness-of-Fit Test larger than 0.05. Even only considering subjects

in each age group, none of the null condition trials had a p-value smaller than 0.05. The largest

difference in horizontal illuminance among null condition trials between two rooms was 5.28 lux,

corresponding to 2.2% of the calibration target; and the largest difference in vertical illuminance

was 3.03 lux, corresponding to 1.8% of the calibration target. These measurements and statistical

findings suggest that the two rooms were very close to each other over the duration of the

experiment.

55

Table 4-1 | Summary data for null condition trials showing percentages of left/right selected. None of

the trials in either age group had a p-value smaller than 0.05; p-values are only shown for the overall

(i.e. age group pooled) category

Null Condition

Trials SPD

Horizontal

Illuminance

(lux)

Left/Right

Age Group

Overall

p-value of the

Chi-Square

Goodness-of-

Fit test Younger Older

1-1 SPX3K 240 Left 43% 43% 43%

0.3017 SPX3K 240 Right 57% 57% 57%

2-2 SPX3K 270 Left 50% 53% 52%

0.7963 SPX3K 270 Right 50% 47% 48%

3-3 SPX3K 300 Left 57% 43% 50%

1.0000 SPX3K 300 Right 43% 57% 50%

4-4 SPX3K 330 Left 57% 47% 52%

0.7963 SPX3K 330 Right 43% 53% 48%

7-7 RevLF 240 Left 40% 43% 42%

0.1967 RevLF 240 Right 60% 57% 58%

10-10 RevLF 270 Left 57% 57% 57%

0.3017 RevLF 270 Right 43% 43% 43%

12-12 RevLF 300 Left 40% 47% 43%

0.3017 RevLF 300 Right 60% 53% 57%

13-13 RevLF 330 Left 43% 40% 42%

0.1967 RevLF 330 Right 57% 60% 59%

Combined null condition trials Left 48% 47% 48%

0.7963 Right 52% 53% 52%

Since the experimental design for the perceived brightness sessions provided complete

counterbalancing, random chance suggests that there should have been an even number of

selections for left/right among all subjects‘ judgments. When disregarding the null condition

56

trials, the left room was selected as brighter 48 percent of the time, which was not statically

different from 50 percent (Chi-Square Goodness-of-Fit Test, p = 0.110)

Because of the experimental design, the position (left/right) of the light setting should have been

independent from the selection made by the subjects. Considering all 16 pairs of light settings

with SPX3K in the left room and RevLF in the right room, the left room was selected 447 times

and the right room was 513 times. For the counterbalanced pairs, with RevLF in the left room and

SPX3K in the right room, the left room was selected 478 times and the right room 482 times. The

Chi-Squared Test of Independence between SPD and location fails to reject the null hypothesis of

independence (p = 0.959). Figure 4-1 provides the data structure for this test when all

comparisons are pooled and Table 4-2 provides individual values for each paired comparison.

Location Sum

Left Right

SPD RevLF 478 513 991

SPX3K 447 482 929

Sum 925 995 1930

Figure 4-1 | Example of Chi-Squared test of independence between SPD and location

(results for all the pairs are summarized in Table 4-2)

57

Table 4-2 | Summary of results for Chi-Squared test of independence. The SPD and location are

statistically independent (p-value>0.05)

Pairs of Light

Settings

Number of

Selection

Pairs of Light

Settings

Number of

Selection p-value of Chi-

Squared test of

independence Left Right Left Right Left Right Left Right

SPX3K 240 lux

RevLF 192 lux

54 6 RevLF 192 lux

SPX3K 240 lux

9 51 0.534

SPX3K 240 lux

RevLF 216 lux

41 19 RevLF 216 lux

SPX3K 240 lux

19 41 1.000

SPX3K 240 lux

RevLF 240 lux

12 48 RevLF 240 lux

SPX3K 240 lux

43 17 0.580

SPX3K 240 lux

RevLF 264 lux

5 55 RevLF 264 lux

SPX3K 240 lux

50 10 0.299

SPX3K 270 lux

RevLF 270 lux

16 44 RevLF 270 lux

SPX3K 270 lux

42 18 0.861

SPX3K 270 lux

RevLF 297 lux

3 57 RevLF 297 lux

SPX3K 270 lux

49 11 0.078

SPX3K 270 lux

RevLF 216 lux

50 10 RevLF 216 lux

SPX3K 270 lux

4 56 0.189

SPX3K 270 lux

RevLF 243 lux

36 24 RevLF 243 lux

SPX3K 270 lux

17 43 0.667

SPX3K 300 lux

RevLF 270 lux

41 19 RevLF 270 lux

SPX3K 300 lux

17 43 0.873

SPX3K 300 lux

RevLF 300 lux

14 46 RevLF 300 lux

SPX3K 300 lux

46 14 1.000

SPX3K 300 lux

RevLF 330 lux

4 56 RevLF 330 lux

SPX3K 300 lux

53 7 0.438

SPX3K 300 lux

RevLF 240 lux

52 8 RevLF 240 lux

SPX3K 300 lux

6 54 0.663

SPX3K 330 lux

RevLF 297 lux

42 18 RevLF 297 lux

SPX3K 330 lux

15 45 0.782

SPX3K 330 lux

RevLF 330 lux

14 46 RevLF 330 lux

SPX3K 330 lux

45 15 0.912

SPX3K 330 lux

RevLF 363 lux

6 54 RevLF 363 lux

SPX3K 330 lux

56 4 0.582

SPX3K 330 lux

RevLF 264 lux

57 3 RevLF 264 lux

SPX3K 330 lux

7 53 0.270

Total 447 513 Total 478 482 0.959

58

Though bias is unavoidable in any experiment, these tests and analyses suggest that the biases

derived from the apparatus, calibration, and experimental design were minimal. All judgments

made by the subjects should be based upon their perception of the light stimuli.

4.2 Perceived Brightness

Judgments made by subjects were recorded as left or right. These data were converted to binary

digits for the statistical analysis, with 0 presenting a vote for SPX3K and 1 for RevLF. The

inverse presentation (for example, Light Setting 1 on the left versus Light Setting 6 on the right,

and Light Setting 6 on the left versus Light Setting 1 on the right) were combined into one data

set, since, as shown above, the location of the stimulus did not affect the judgments made by the

subjects. The counts in each pair were summed and the percentage values computed. Thus, for

each illuminance level of the SPX3K, four percentage values of the subjects‘ votes for the RevLF

were computed (i.e. one for each illuminance ratio), as summarized in Table 4-3. Since the

subject gave a forced-choice response for each pair of light settings, the sum of percentages for

each pair is 100%. Table 4-3 and Table 4-4 summarize the percentage of votes for the younger

and older groups. All the counts in these two tables, except two counts in the shaded cells, are

statistically different from chance according to the Chi-Square Goodness-of-Fit Test (p > 0.05).

Percentage of votes versus illuminance ratio is plotted for each illuminance level of SPX3K, with

Figure 4-2 for younger group and Figure 4-3 for older group. These figures include two

regression lines per plot, one for each lamp type. The illuminance ratio for equal brightness at

each illuminance level of SPX3K can be interpolated as the intersection of the regression lines.

This point represents the illuminance ratio at which we would expect 50% of the votes for

59

RevLF, and 50% of the votes for SPX3K. Figure 4-2 and Figure 4-3 are plots of the data in Table

4-3 and Table 4-4, with one for each tabulated row of data.

Table 4-3 | Percentage of votes in younger group at different illuminance levels of SPX3K

Illuminance

Level of

SPX3K

Percentage of Votes for a SPD at Different Iilluminance Ratios

RevLF SPX3K

80% 90% 100% 110% 80% 90% 100% 110%

240 6.7% 23.3% 73.3% 88.3% 93.3% 76.7% 26.7% 11.77%

270 6.7% 28.3% 63.3% 86.7% 93.3% 71.7% 36.7% 13.3%

300 10.0% 28.3% 70.0% 90.0% 90.0% 71.7% 30.0% 10.0%

330 8.3% 18.3% 75.0% 90.0% 91.7% 81.7% 25.0% 10.0%

Overall 7.9% 24.6% 70.4% 88.8% 92.1% 75.4% 29.6% 11.2%

Table 4-4 | Percentage of votes in older group at different illuminance levels of SPX3K ( The shaded

cells in emboldened values represent results that are not statistically different from chance according

to the Chi-Square Goodness-of-Fit test with p-values > 0.05)

Illuminance

Level of

SPX3K

Percentage of Votes for a SPD at Different Illuminance Ratios

RevLF SPX3K

80% 90% 100% 110% 80% 90% 100% 110%

240 18.3% 40.0% 78.3% 86.7% 81.7% 60.0% 21.7% 13.3%

270 16.7% 40.0% 80.0% 90.0% 83.3% 60.0% 20.0% 10.0%

300 13.3% 31.7% 83.3% 91.7% 86.7% 68.3% 16.7% 8.3%

330 8.3% 36.7% 76.7% 93.3% 91.7% 63.3% 23.3% 6.6%

Overall 14.2% 37.1% 79.6% 90.4% 85.8% 62.9% 20.4% 9.6%

60

(a)

(b)

(c)

(d)

Percentage of votes that stated RevLF brighter than SPX3K

Percentage of votes that stated SPX3K brighter than RevLF

Log. (Percentage of votes that stated RevLF brighter than SPX3K)

Log. (Percentage of votes that stated SPX3K brighter than RevLF)

Figure 4-2 | Plot of percentage of votes versus illuminance ratios at different illuminance levels of

SPX3K for younger group

(a. 240 lux; b. 270 lux; c. 300 lux; d. 330 lux)

0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s

Illuminance Ratio (RevLF / SPX3K)

0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s


0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s


0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s


61

(a)

(b)

(c)

(d)






SPX3K for older group


0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s


0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s


0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s


0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

Pe

rce

nta

ge o

f V

ote

s


62

Table 4-5 | Summary of the regression lines and hypothesis testing for the plots of younger and older

groups

Age

Group

Illuminance

of SPX3K

(lux)

Regression Results for

the Percentage of

Votes for RevLF Illuminance

Ratio at the

Intersection

Point

Mean of the

Illuminance

Ratios

p-value of testing

Regression

Model R

2

Equal

Slopes

Equal

Intercepts

Younger

240 y = 2.775

ln(x) + 0.6409

94.9% 95.1%

95.1% 0.975 0.961

270 y = 2.585

ln(x) + 0.6132

98.8% 95.7%

300 y = 2.647

ln(x) + 0.6501

97.1% 94.5%

330 y = 2.831

ln(x) + 0.6442

91.4% 95.0%

Older

240 y = 2.301

ln(x) + 0.6925

95.9% 92.0%

92.4% 0.786 0.961

270 y = 2.458

ln(x) + 0.7100

96.4% 91.8%

300 y = 2.705

ln(x) + 0.7077

93.2% 92.6%

330 y = 2.786

ln(x) + 0.6999

98.4% 93.1%

Table 4-5 summarizes the regression models. The illuminance ratios for equal brightness at each

illuminance of SPX3K were computed. For the subjects in the younger group, the illuminance

ratios of RevLF to SPX3K range within 94.5% to 95.7%; and for the subjects in the older group,

the ratios range within 91.8% to 93.1%. Within each group, the four regression lines are not

63

statistically different from each other (all p-values for testing equal slopes and intercepts are

larger than 0.05), which is also supported by the ANOVA results that show that illuminance ratio

was not a significant factor affecting the percentage of votes. It is possible to pool the data from

these four illuminance levels of the SPX3K for each age group, as shown in the last rows in Table

4-3 and Table 4-4. Figure 4-4(a) and (b) plots and regression lines for the younger and older

subject groups using the pooled data. A Student‘s Paired Sample t-test suggests a statistical

difference in the percentage of votes between the younger and older age groups, indicating a

different illuminance ratio for equal brightness. The illuminance ratios of the intersection points

are 95.1% for the younger group and 92.4% for the older group.

(a)

(b)





Figure 4-4 | Plot of percentage of votes versus illuminance ratios (a. younger age group; b. older age

group)

0%

20%

40%

60%

80%

100%

120%

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120%

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64

Thus, within an illuminance range of 240 to 330 lux, these data suggest that equal brightness will

occur in an environment illuminated with RevLF when they provide 5% (for occupants of ~ 20

years) and 8% (for occupants of ~ 80 years) lower illuminance than a similar environment

illuminated with SPX3K. More than likely, for occupants between the ages of 20 and 80, the

illuminance could be lowered within the range of 5 to 8%. Since the trends were so stable at 240,

270, 300 and 330 lux, and because all of these are conditions of photopic adaptation, we would

expect to find similar ratios over a wider range of photopic conditions.

Cataract Surgery

Twenty of the subjects in the older group had had cataract surgery and their responses can be

analyzed against those that had not. Summary tables and figures are provided as Figure 4-6,

Figure 4-7, Table 4-6, and Table 4-7.

Table 4-6 | Percentage of votes of 10 older subjects without cataract surgery at different illuminance

levels of SPX3K

Illuminance

Level of

SPX3K


RevLF SPX3K

80% 90% 100% 110% 80% 90% 100% 110%

240 20.0% 40.0% 75.0% 90.0% 80.0% 60.0% 25.0% 10.0%

270 15.0% 40.0% 70.0% 95.0% 85.0% 60.0% 30.0% 5.0%

300 15.0% 20.0% 90.0% 95.0% 85.0% 80.0% 10.0% 5.0%

330 10.0% 35.0% 80.0% 95.0% 90.0% 65.0% 20.0% 5.0%

Overall 15.0% 33.8% 78.8% 93.8% 85.0% 66.2% 21.2% 6.2%

65

Table 4-7 | Percentage of votes of 20 older subjects with cataract surgery, including three with

abnormal color vision, at different illuminance levels of SPX3K

Illuminance

Level of

SPX3K


RevLF SPX3K

80% 90% 100% 110% 80% 90% 100% 110%

240 18.0% 40.0% 80.0% 85.0% 82.0% 60.0% 20.0% 15.0%

270 18.0% 40.0% 85.0% 88.0% 82.0% 60.0% 15.0% 12.0%

300 13.0% 38.0% 80.0% 90.0% 87.0% 62.0% 20.0% 10.0%

330 8.0% 38.0% 75.0% 93.0% 92.0% 62.0% 25.0% 7.0%

Overall 13.8% 38.8% 80.0% 88.8% 86.2% 61.2% 20.0% 11.2%

(a)

(b)

0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

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0%

20%

40%

60%

80%

100%

120%

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(c)

(d)






SPX3K for the older subjects without cataract surgery


(a)

(b)

0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

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0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

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0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

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Illuminance Ratio (RevLF / SPX 3000K)

0%

20%

40%

60%

80%

100%

120%

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(c)

(d)






SPX3K for the older subjects with cataract surgery


0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

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0%

20%

40%

60%

80%

100%

120%

0.7 0.8 0.9 1 1.1 1.2

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Table 4-8 | Summary of the regression lines and hypothesis testing for the plots of subjects with and

without cataract surgery

Cataract

Surgery

Illuminance

of SPX3K

(lux)

Regression Results

for the percentage of

votes for RevLF Illuminance

Ratio at

Intersection

Point

Mean of the

Illuminance

Ratios

p-value of testing

Regression

Model R

2

Equal

Slopes

Equal

Intercepts

Without cataract surgery

240 y = 2.309

ln(x) + 0.6971

97.9% 91.8%

92.4% 0.809 0.998

270 y = 2.540

ln(x) + 0.6980

99.6% 92.5%

300 y = 2.913

ln(x) + 0.7198

84.7% 92.7%

330 y = 2.831

ln(x) + 0.7150

97.2% 92.7%

With cataract surgery

240 y = 2.283

ln(x) + 0.6906

94.3% 92.0%

92.2% 0.822 0.990

270 y = 2.416

ln(x) + 0.7184

92.7% 91.4%

300 y = 2.582

ln(x) + 0.7030

96.3% 92.4%

330 y = 2.758

ln(x) + 0.6958

99.0% 93.1%

Table 4-8 summarizes the regression models. The illuminance ratios for equal brightness at each

illuminance of SPX3K were computed. For the subjects without cataract surgery, the illuminance

ratios of RevLF to SPX3K range within 91.8% to 92.7%; and for the subjects with cataract

surgery, the ratios range within 91.4% to 93.2%. Within each group, four regression lines are not

69

statistically different from each other (all p-values for testing equal slopes and intercepts are

larger than 0.05), which is also supported by the ANOVA results that show that illuminance ratio

was the only factor affecting the percentage of votes. It is possible to pool the data from these

four illuminance levels of the SPX3K for each group, as shown in the last rows in Table 4-6 and

Table 4-7. Figure 4-7 (a) and (b) plot the data and regression lines for the older subjects with and

without cataract surgery using the pooled data.

A Student‘s Paired Sample t-test suggest no statistical difference in the responses of the older

subjects with and without cataract surgery, indicating the same illuminance ratio for equal

brightness. Irrespective of whether or not the older subject had cataract surgery, the illuminance

ratio for equal brightness is 92.4%, which is statistically different from 100%.

To conclude, within an illuminance range of between 240 to 330 lux, these data suggest that equal

brightness will occur in an environment illuminated with RevLF when they provide about 8%

lower illuminance than the SPX3K for occupants with a mean age of ~ 80. This result was not

affected by whether or not the older subject had cataract surgery.

70

(a)

(b)





Figure 4-7 | Plot of percentage of votes versus illuminance ratios (a. older subjects without cataract

surgery; b. older subjects with cataract surgery)

Preference

67% of the younger subjects and 73% of the older subjects preferred the room illuminated by the

RevLF when they stepped into the rooms. No difference was found between preference of the two

age groups (Chi-Squared Test of Independence, p = 0.573). The difference between the

preference for the room illuminated by the RevLF versus the SPX3K was significantly different

(Chi-Square Goodness-of-Fit test, p = 0.002). Color preference and brightness were cited as the

major reasons for this preference.

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20%

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60%

80%

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Total Error Score (TES), Red-Green Partial Error Score (R-G PES), and Blue-Yellow Partial

Error Score (B-Y PES) were recorded for each subject under each light setting. The results were

analyzed using the Minitab® 15 statistical software packages. The average of TES, R-G PES, and

B-Y PES of the subjects with normal color vision in each group under each light setting are given

in Table 4-9. Figure 4-8 (a) is a graph of younger group under each light setting, including 95%

confidence interval bars; Figure 4-8 (b) is a graph of the older group.

Table 4-9 | Summary of the results of FM-100 of the subjects with normal color vision in each age

group under each light setting

Age Group SPX3K RevLF

R-G PES B-Y PES TES R-G PES B-Y PES TES

Younger 22.52 24.79 47.31 13.41 30.17 43.59

Older 44.67 79.63 124.30 33.93 94.81 128.74

(a)

0 50 100 150 200

R-G PES

B-Y PES

TES

RevLF

SPX3K

72

(b) Figure 4-8 | The mean Total Error Score (TES), Red-Green Partial Error Score (R-G PES), and

Blue-Yellow Partial Error Score (B-Y PES) of the subjects with normal color vision in each age

group for the FM-100 under each light setting, shown with individual 95% confidence interval bars

The higher the error score, the worse the color discrimination performance. Figure 4-8 illustrates

that younger subjects performed better than the older subjects under both light settings. And

visually, R-G PES was decreased and B-Y was increased under illumination provided by RevLF.

However, there was not a large difference in TES between the two light settings.

ANOVA

SPD, age group, and cataract surgery were considered as factors affecting R-G PES, B-Y PES,

and TES. The ANOVA tables are shown in Table 4-10, Table 4-11, and Table 4-12. These tables

are interpreted by looking at the p-value; when it is smaller than 0.05 the null hypothesis of no

effect can be rejected with 95% confidence.

0 50 100 150 200

R-G PES

B-Y PES

TES

RevLF

SPX3K

73

These results suggest that age and cataract surgery are significant factors affecting color

discrimination performance on the FM-100 test for subjects with normal color vision, including

discrimination ability for red-green colors, yellow-blue colors, and the overall performance. The

older subjects always had worse performance than the younger subjects. This result provides

statistical confirmation of the plots given in Figure 4-8. This result is consistent with previous

results found by others [66, 68, 69].

Table 4-10 | Analysis of variance for R-G PES

Source Df Seq SS Adj SS Adj MS F p-value

Cataract 1 730.3 4730.7 4730.7 8.85 0.004

Age 1 16724.2 16724.2 16724.2 31.29 <0.001

SPD 1 2740.3 2740.3 2740.3 5.13 0.026

Error 108 57720.1 57720.1 534.4

Total 111 77915.0

Table 4-11 | Analysis of Variance for B-Y PES


Cataract 1 5331 38530 38530 20.63 <0.001

Age 1 132998 132998 132998 71.21 <0.001

SPD 1 2860 2860 2860 1.53 0.219

Error 108 201722 201722 1868

Total 111 342911

Table 4-12 | Analysis of Variance for TES


Cataract 1 10007 70262 70262 17.76 <0.001

Age 1 244047 244047 244047 61.68 <0.001

SPD 1 1 1 1 0 0.986

Error 108 427298 427298 3956

74

Total 111 681354

Student’s Paired Sample t-test

In order to improve the precision of the analysis, Student‘s Paired Sample t-tests were employed

for subgroups of the sample: younger subjects; older subjects with cataract surgery; and older

subjects without cataract surgery. Each subject was regarded as a block in these analyses. Table

4-13 summarizes the results of these analyses.

Table 4-13 | Summary of the results of Student’s Paired Sample t-tests

Group N

Student’s

Paired Sample

t-test

Mean

Difference

(RevLF

minus

SPX3K)

t-value p-value

Younger subjects 29

R-G PES -9.10 -4.51 <0.001

B-Y PES 5.38 1.69 0.102

TES -3.72 -1.02 0.316

Older subjects with cataract

surgery 17

R-G PES -11.41 -3.03 0.008

B-Y PES 13.24 2.06 0.056

TES 1.82 0.19 0.848

Older subjects without cataract

surgery 10

R-G PES -9.60 -1.61 0.142

B-Y PES 18.5 1.75 0.114

TES 8.9 0.66 0.524

Clearer results can be drawn from the Student‘s Paired Sample t-tests:

The RevLF was able to decrease the Red-Green Partial Error Score (i.e. improve the

color discrimination ability for red and green colors of the FM-100 test) in comparison to

75

the SPX3K for the subjects below 25 years of age and the subjects with cataract surgery

above 60 years of age.

No statistically significant effect was found between the RevLF and SPX3K on overall

color discrimination ability or the ability to discriminate blue and yellow colors.

Color-deficient Subjects

Four subjects in this study were tested to have abnormal color vision, with one in the younger

group and three in the older group. Table 4-14 summarizes the FM-100 results of the color-

deficient subjects in each age group. Though some differences can be observed between two

SPDs, the sample size was not large enough to make statistically sound inferences.

Table 4-14 | Summary of the results of FM-100 of the color-deficient subjects in each age group

under each light setting

Age group

SPX3K RevLF

R-G

PES

B-Y

PES TES

R-G

PES

B-Y

PES TES

Younger 285 259 544 296 308 604

Older 83.7 132.3 216.0 78.3 185.7 264.0

Cataract Surgery

Figure 4-9 (a) graphs the error scores for the older subjects with cataract surgery under each light

setting, with 95% confidence interval bars; Figure 4-9 (b) is a graph of the older subjects without

cataract surgery. Cataract surgery was a significant factor affecting color discrimination ability.

The subjects with cataract surgery performed better than those without cataract surgery, having

lower R-G PES, B-Y PES, and TES.

76

(a)

(b)

Figure 4-9 | The mean Total Error Score (TES), Red-Green Partial Error Score (R-G PES), and

Blue-Yellow Partial Error Score (B-Y PES) of the subjects in older group for the FM-100 under each

light setting, shown with individual 95% confidence interval bars.

0 50 100 150 200 250 300

R-G PES

B-Y PES

TES

RevLF

SPX3K

0 50 100 150 200 250 300

R-G PES

B-Y PES

TES

RevLF

SPX3K

77

Chapter 5 Discussion

5.1 Perceived Brightness

The benefits of the RevLF, in terms of brightness-per-lumen and enhanced red-green color

discrimination, can be considered in terms of the opponent process of the visual system

established by De Valois [75], as shown in Figure 5-1.

Figure 5-1 | Neural Opponent Signals & SPDs of two lamps

The SPX3K has little energy within the ‗green‘ spectral region from 500 to 550 nm. Modification

on this spectrum to help the RevLF SPD increase the red-green opponent-process signals (Figure

5-2(a)), while slightly reducing the blue-yellow opponent-process signals (Figure 5-2(b)). By

scaling the two lamps to provide the same amount of lumens, the ratio of the total red-green

opponent-process signals of RevLF to SPX3K is 1.22 and the ratio of the total blue-yellow is

1.01.

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

350 400 450 500 550 600 650 700 750 800Ou

tpu

t

Wavelength (nm)

Red-Green Opponent

Blue-Yellow Opponent

RevLF

SPX3K

78

(a)

(b)

SPX3K

RevLF

Figure 5-2 | Opponent signals adapted to the SPX3K and the RevLF

( a. Red-green opponent signal; b. Blue-yellow opponent signal )

-0.5

0

0.5

1

1.5

2

350 400 450 500 550 600 650 700 750 800

Sign

al

Wavelength (nm)

-2

-1.5

-1

-0.5

0

0.5

350 400 450 500 550 600 650 700 750 800

Sign

al

Wavelength (nm)

79

Table 5-1 | Lighting metrics and colorimetric properties of two SPDs. The calculations were based on

the average SPDs.

Metrics SPX3K RevLF

CIE 1931 Chromaticity X Coordinate 0.436 0.449

CIE 1931 Chromaticity Y Coordinate 0.386 0.377

CCT 2858 2577

CRI 86 61

R9 -2 29

CQS [76-78] 80.3 66.9

CCT Factor [76-78] 79.1 64.6

Fiedlity Index [76-78] 76 58

Preference Index [76-78] 88 85

Relative Gamut Area of 15 Color Samples [76-78] 104 117

S/P 1.32 1.58

FM Gamut 40.84 36.65

CDI 68.1 77.4

Gamut Area of 8 Color Test Samples of CRI

0.0034 0.0039

Luminous Efficacy of Radiation 336 316

u' 0.258 0.271

v' 0.514 0.512

Cone Surface Area [79] 0.0344 0.0357

Guth [36] 0.377014 0.371544

Thornton [30] 0.462210 0.451348

Howett [80] 0.000357 0.000376

Some have suggested that CCT is a good predictor of brightness perception, with the belief that

higher CCT illumination will be perceived as brighter [23]. Hu and Houser demonstrated that

80

CCT and brightness perception are not related [28], and recent work reasserts that they are not

related [48]. Although this study did not set out to demonstrate a specific hypothesis about CCT,

it provides further evidence that environments illuminated with lamps of lower CCT can be

perceived as brighter than environments illuminated with lamps of higher CCT when V(λ)-based

quantities are equal.

In a review of lamp color properties and brightness perception, Fotios concluded that rooms

illuminated with lamps of higher CRI would appear brighter than those illuminated with lamps of

lower CRI when CCT is similar [29]. However, his analysis also suggested that no general

relationship existed between CRI and brightness perception. The ratio of scotopic to photopic

lumens (a.k.a. S/P ratio) has been promoted by some to predict brightness perception, using the

expression P(S/P)0.5 [81]. Houser and his colleagues illustrated the failure of this expression to

predict the brightness perception [48]. The results found in this study indicate 95% and 92%

illuminance ratio of RevLF to SPX3K will have equal brightness, which is supposed to have

equal P(S/P)0.5 for two lamps based on this theory. The ratios of the P(S/P)0.5 of RevLF to SPX3K

are 1.04 and 1.01 for these two illumiannce ratios, which are not significantly different from 1.

Sometimes, P(S/P)0.5 can be used to predict brightness, like the lamp pairs used in this study, but

it cannot support the theory that P(S/P)0.5 is a good predictor of brightness.

Boyce proposed an equation based on the gamut area of the eight CIE test sample colors

employed in the computation of CRI as a predictor of the illuminance ratio of two lamps that will

yield equal brightness perception [82]:

𝐸1𝐸2= 1.0− 0.6 log10(

𝐺1𝐺2)

Where 𝐸1𝐸2

is the illuminance ratio of two lamps;

81

G1 and G2 are the gamut areas of the two lamps.

The illuminance ratio of RevLF to SPX3K computed from this equation is 96.5%. Though there

is some difference between the results from this equation and from this study, this study still

supported that the lamps having larger gamut area of the eight CIE test sample colors are

perceived brighter.

Both of the S/P ratio and the Gamut Area theory are correctly predicting the direction of the

brightness perception, but the magnitudes of the improvement are not accurate.

Thornton established the prime color theory, which first evolved from his work in fluorescent

lamp development, and was later refined with his experiments that employed heterochromatic and

Maxwell method color matching. One form of heterochromatic brightness matching employs two

visual-fields and four spectral lights, two in each visual-field. Consider any three randomly

selected spectral lights that do not form a line on a chromaticity diagram. If two illuminate one

visual field (i.e. the reference field), and the third is placed in the other visual field (i.e. the test

field), a fourth spectral light must be added to the test field in order to create a visual match.

Thornton showed that when the two illuminants are visually matched in brightness and color by

adjusting the relative powers of the four spectral lights, the least amount of power is required

when that fourth (variable) spectral light it is at or near 450, 530, or 610 nm. He coined the term

‗prime-color‘ for these three spectral regions, and suggested that these represent the peak

underlying spectral sensitivities of the eye-brain system [83]. In this same body of work,

Thornton identified the intermediate spectral regions at or near 500 and 570-580 nm as being

deleterious to brightness and the ability to make color matches. These spectral regions required

the greatest amount of power to make visual matches. He coined the term ‗anti-prime‘ for these

spectral regions [84]. Thornton noted that the anti-prime spectral region near 580 nm was

82

especially harmful to color and brightness perceptions [32]. Perhaps counterintuitively, his results

suggest that removing optical radiation from this spectral region would enhance color and

brightness perception, which is incompatible with the additivity of luminance.

Both of the RevLF and the SPX3K lamps have spectral peaks at 435 and 610 nm, which are near

the nominally ‗blue‘ and ‗red-orange‘ prime-color spectral regions. The SPX3K also has peaks at

490, 545, and 585 nm, while the RevLF has two peaks at 515 and 545 nm. After scaling the SPD

of the SPX3K and RevLF to produce the same amount of lumens, the power contained within the

SPD of the SPX3K lamp from 450 to 600 nm is 1.08 times the power of the RevLF. The peaks of

the SPX3K SPD that are near 490 and 585 nm are near the anti-prime spectral regions.

Conversely, the two peaks of the RevLF SPD are near the central prime-color region, which,

according to Thornton‘s prime-color theory, maximizes brightness perception per watt of optical

radiation. The findings in this study are consistent with Thornton‘s prime-color theory.

Three linear brightness models are also listed in Table 5-1, all of which are based on the

opponent-process model of the visual system. Guth and Thornton‘s models failed to predict the

direction of the brightness trend that we found. These linear brightness models were developed

more than 25 years ago. It is now widely agreed that brightness perception is non-linear. Still,

even a non-linear model should be expected to correctly order SPDs presented at constant

luminance, the relationship between opponent signals and perception of brightness needs further

investigation.

As people age, the visual system changes gradually, including changes to the lens, vitreous and

aqueous humors, retina, and range of pupil dilation and constriction. These changes should be

expected to affect brightness perception, color discrimination, visual acuity, and non-visual

biological responses. The transmittance of the lens is an especially important consideration,

83

especially in the short wavelengths. Our data suggests that the RevLF lamp would be more

beneficial, in terms of brightness perception, to seniors than to younger people RevLF. This may

be because the RevLF emits proportionally more radiation in short-wavelength region, which

may explain why the older subjects required lower illuminance for equal brightness, in

comparison to the younger subjects.

Cataract surgery is the removal of the natural lens of the eye. An artificial intraocular lens implant

is inserted into the eye after the surgery. This lens removal and replacement increases

transmittance, but this improvement in optical performance is not the only change. The biological

performance of the eye may also be improved, such as a reduction in dry eye [85]. Ikeda

mentioned that it was natural to suppose that the older people above 71.9 years of age had the

cataract in their eyes, though it might not be clear in the ophthalmoscope test [86].

Ikeda asked one subject to perform heterochromatic brightness matching before and after

cataract surgery [86]. Some differences were found between the results before and after the

surgery on the right eye, while no difference was found on the left eye. Kitakawa showed that the

length of time after the cataract surgery affects the color appearance of the objects to the

subjects, especially due to optical radiation in the short-wavelength region [87]. Different types of

intraocular lenses have different transmission properties. All of these factors may contribute to

the fact that cataract surgery had no effect on the illuminance ratio for equal brightness in this

study.

The efficacy of a lamp is defined as the ratio of the total luminous flux emitted by the lamp to the

total input power, which is expressed in lumens per watt (lm/W). For most conventional light

sources, lamp efficacy is the product of three components: radiant efficiency, radiation efficiency,

and luminous efficacy of radiation (LER). The radiant efficiency is defined as the ratio of the

84

radiant power to the total power consumed by the lamp. The radiation efficiency is defined as the

ratio of the radiant power in the visible region to the total power radiated by the lamp. LER is

defined as the ratio of the total luminous flux emitted to the total power within the visible region.

LER depends only on the SPD of the lamp in the visible spectrum.

The LER of the RevLF lamp is 94% of the LER of the SPX3K lamp. Coupled with the result that

the RevLF required 5 to 8% lower illuminance than the SPX3K for equal brightness, the RevLF

could theoretically provide equivalent brightness perception with 11 to 14% fewer watts, but only

if the conversion efficiency of both lamps were equivalent. However, the efficacy of the RevLF

lamp is only 79% of the SPX3K lamp. On the basis of brightness perception per input watt, the

advantage brought by the SPD of the RevLF is not offset by its lower efficacy. Said another way,

though a room illuminated with RevLF lamps requires a lower illuminance than a room

illuminated with SPX3K lamps when equal brightness is desired, the lower illuminance still

requires more power.

Though brightness is an important criterion for design, it may not always be the sole or even

primary consideration. Preference is important too. After the side-by-side comparison of

brightness, each subject stepped into the rooms to evaluate personal preference. The question

heard by the subjects was ―which room do you prefer‖, so the responses and reasons given by the

subjects should reflect the subjects‘ overall impression and feeling. Most subjects preferred the

room illuminated by the RevLF, citing color and/or brightness. The major reasons given by those

who preferred the room illuminated by the SPX3K were the same: color and brightness. Most of

the subjects who preferred the color of the room illuminated by the SPX3K were Asian, since

they generally prefer higher CCT [88]. Some of the subjects who preferred the room illuminated

by the SPX3K stated that the room illuminated by the RevLF was too bright. The illuminance

85

level was 330 lux when the subjects were asked to make a choice based on preference, which was

the highest illuminance employed in the study. It is possible that a higher percentage would have

preferred the room illuminated by the RevLF lamps if the forced choice comparison was made at

an illuminance of 300 or 270 lux.

Both the brightness comparisons and preference judgments took place in a neutral grey

environment, with grey walls, white ceilings, and grey carpet. The RevLF does not only increase

the red-green opponent signals (which likely contributes to increased brightness perception), it

also increases the red-green color contrast of lighted objects. If the evaluations had been

performed in a colorful environment, it is possible that the RevLF would have had an even

greater advantage. It is plausible that the same level of clarity and satisfaction could be reached at

a lower illuminance with a lamp type having SPD that enhances chromatic contrast by enhancing

the opponent signals. Such visual phenomenon have the potential to reduce energy if they can be

achieved at the same conversion efficiency as lamp designs optimized for V(λ) and CRI.


No statistical difference of TES was found between the RevLF and SPX3K lamps for either age

group, indicating similar color discrimination performance as characterized by the FM-100 test.

CDI, CRI, Gamut Area, and Farnsworth Munsell (FM) Gamut Area for the RevLF and SPX3K

lamps are listed in Table 5-1, predicting unequal colorimetric performance. The failure of the

CRI, CDI, or FM Gamut Area to predict TES is consistent with the results found by Royer and

his colleagues, who found that neither CRI, CDI, or FM Gamut Area was able to correctly order,

let alone correlate with, the TES of the FM-100 test under four types of illumination (i.e. two

types of linear fluorescent, tri-band LED, halogen). They questioned the concept of using gamut

area to characterize color discrimination [63].

86

R9 is one of the special indices in the CRI system; it is intended to characterize the ability of an

illuminant to render saturated reds. The SPX3K has an R9 value of -2, while the RevLF has a

value of 29. The difference in R9 indicates that the RevLF illumination is more similar to the

blackbody reference than the SPX3K illumination. Fidelity index and preference index are two

special indices in the CQS system established by NIST [76-78]. Fidelity index is calculated

without the saturation factor; while the preference index gets credit for increase of saturation. By

comparing the fidelity indices and the preference indices of the two lamps, it can be seen that the

RevLF gets more benefit when saturation is considered.

Figure 5-3 illustrates the gamut areas of the 85 FM samples under SPX3K and RevLF

illumination in the CIE 1960 UCS; the two lamps shift the gamut area in different ways. The

SPX3K shifts and expands the gamut toward violet / blue and yellow, while the RevLF shifts and

expands the gamut toward red. The difference between the gamut areas in the red region is

sharper than that in the violet / blue and yellow regions. The sharpness of the regional gamut

differences may account for why the R-G PES was statistically better under RevLF illumination,

but the B-Y PES was not.

87

SPX3K

RevLF

Illuminant C

Spectrum Locus

Figure 5-3 | FM Gamut Area shown in the CIE 1960 UCS for the RevLF, the SPX3K, and CIE

Illuminant C ( Illuminant C is the reference source under which the samples have approximately

equal spacing)

The 85 FM-100 samples have approximately equal spacing under Illuminant C in the CIE 1960

UCS. A sudden change in the direction in the CIE 1960 UCS between adjacent caps is a likely

cause of a sorting error. Figure 5-4 shows the chromaticity coordinates of FM-100 samples 13

through 33, which are the green caps, illuminated by RevLF and SPX3K illumination. It is

apparent that there are several sudden changes in direction when these caps are illuminated by

SPX3K lamps, which likely contributed to the higher error scores in these caps. For all other

caps, the changes in direction are similar under SPX3K and RevLF. The standard deviations of

the spacing between the red-green caps also indicate a large difference between RevLF and

0.25

0.30

0.35

0.40

0.10 0.15 0.20 0.25 0.30 0.35 0.40

v

u

88

SPX3K, which are listed in Table 5-2. The graphical representation of the color chips shown in

Figure 5-3 and the standard deviations shown in Table 5-2 have potential to predict color

discrimination ability, are ripe to be considered in a future color discrimination measure, and may

be useful as spectral design tools.

Table 5-2 | Standard deviations of the caps of three SPDs

SPD Red-green caps Blue-yellow caps All 85 caps

CIE Illuminant C 0.001391 0.001091 0.001304

RevLF 0.002423 0.002846 0.003231

SPX3K 0.003266 0.002864 0.003077

SPX3K

RevLF

Blackbody locus

Spectrum Locus

Figure 5-4 | Plots of the chromaticity coordinates of FM sample 14 to sample 33 lit by the RevLF and

the SPX3K in the CIE 1960 UCS

0.33

0.34

0.35

0.36

0.37

0.38

0.24 0.25 0.26 0.27 0.28 0.29 0.30 0.31 0.32 0.33 0.34 0.35 0.36

v

u

89

As shown in Figure 5-2 (a), the modification associated with the RevLF SPD increases the red-

green opponent signals. Thus, the contrast between red and green colors is improved, which is

beneficial to the color discrimination of red and green colors. At the same time, the spectrum

modification reduces blue-yellow signals (Figure 5-2 (b)), which reduces contrast between yellow

and blue colors, leading to poorer color discrimination for yellow and blue colors. However, our

statistical results show only a significant improvement in color discrimination for red-green

colors by the RevLF. Neither overall color discrimination ability nor the ability for blue-yellow

colors was found to be improved under illumination of RevLF.

The improvement of the red-green color discrimination ability is expected to be beneficial to

people with red-green color deficiency. The extent of the improvement would be expected to

relate to the degree of a person‘s color deficiency. We cannot make any conclusions from this

study since the number of the color-deficient subjects was too small.

Age and cataract surgery were found to affect color discrimination scores. The older subjects

performed worse than the younger subjects, and the older subjects without cataract surgery

performed worse than the older subjects with cataract surgery. As mentioned previously, the lens

yellows with age, which distorts the SPD of the light received by the photoreceptors and reduces

the illuminance on the retina. The distortion of the SPD and the reduction in transmittance

decrease the opponent signals and color contrasts. After cataract surgery, transmittance improves

and the distortion disappears, and saturation increases, which all allow for better color contrasts

[89]. Whether or not RevLF is able to improve color discrimination in older subjects depends on

whether or not they had cataract surgery. The results suggest that RevLF is effective in improving

color discrimination for older people with cataract surgery, but is not for the older people without

90

cataract surgery. While true, on average, the results may not be true for all individual cases since

transmittance properties vary between lenses.

An illuminance of 300 lux was chosen for this study. Boyce and Simons found that illuminance

did not affect the color discrimination performance as characterized with the FM-100 test when

illuminance was in the range of 300 to 1200 lux. The results found in this study are expected to

remain valid for a wider range of illuminance levels, especially for younger people. Illuminance

is a consideration for elders since improved color discrimination performance has been shown by

increasing illuminance from 400 lux to 1200 lux [66].

Color discrimination was characterized in this study using the FM-100 test. Though the FM-100

is the most widely used test for color discrimination, all of the caps are equal in chroma and have

modest saturation. The real world contains not only medium-saturated colors, but also de-

saturated and saturated colors. In the future, it would be worth employing colors with different

levels of saturation, which may further bracket and characterize color discrimination under

different spectra.

91

Chapter 6 Conclusions

RevLF can be set to an illuminance that is about 5% or 8% lower than SPX3K for equal

brightness, within the range of 240 to 300 lux, in a colorless / neutral space perceived by

people below 25 years of age or people above 60 years of age, respectively. This

conclusion can likely be generalized for a wider range of illuminance, so long as the

observer is photopically adapted.

Based on the side-by-side experimental method, and at the same illuminance of 330 lux,

the room illuminated by RevLF was more preferred than an otherwise identical room

illuminated by SPX3K by a margin of 2 to 1. Subjects cited color and brightness

perception as the reasons for their preference.

When brightness perception is considered in isolation, the advantage of the SPD for the

RevLF (again, for brightness only) cannot offset the disadvantage of its lower efficacy.

At equal brightness, a room illuminated with RevLF will consume more energy than the

same room illuminated by SPX3K.

When brightness and color discrimination are considered together, as with visual clarity,

it is unknown whether or not RevLF or SPX3K illumination would be more energy

efficient. Preference also plays a role in the gestalt evaluation.

At 300 lux, no significant difference in overall color discrimination as characterized by

the FM-100 test was found under RevLF and SPX3K illumination. In comparison to

SPX3K illumination, RevLF illumination improved red-green color discrimination for

color-normal people below 25 years of age, and for those above 60 years of age who had

cataract surgery. This result is expected to be valid for a wider range of illuminance

levels.

92

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effects of spectral modification on perceived brightness

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