eng05 stakeholder presentation - national physical laboratory · 2013. 5. 22. · laboratoire...

Laboratoire national de métrologie et d’essais

ENG05 Stakeholder

Presentation


ENG05 – Stakeholder Presentation April 24th 2013 – NPL Teddington

WP3 : Human Perception of SSL D. RENOUX - presenter – LNE(*)

J.NONNE – LNE (*)

G.ROSSI - INRIM (**) P.IACOMUSSI - INRIM (**)

D.SABOL - SMU (***) M.SMID – CMI (****)

(*) French NMI - (**) Italian NMI – (***) Slovak NMI – (****) Czech NMI


WP3 : Human Perception of SSL

WP1: Traceability for SSL Measurements WP2: Basic measurement methods for SSL characterisation WP3: Human perception of SSL Task 3.1 : Colour rendering Task 3.2 : Visual comfort Task 3.3 : Mesopic vision for outdoor lighting

WP4: Quality metrics for SSL characterisation WP5: Creating impact WP6: JRP Management and Coordination


The study on colour rendering was carried out following steps 1 to 6 for the ENG05, LNE will continue to work on step 7 to 8. We present today the achieved steps (1->5) and the direction of the step in progress (6).

1. reviewing and analysing all proposals of metrics, 2. implementing relevant metrics, 3. applying implemented metrics on a collection of SPDs, 4. performing a real life subjective experiment in a real size test room, 5. processing and comparing subjective ratings with metric’s predictions, 6. complementing and/or supplementing current CIE CRI index with refined

proposals for a better correlation with subjective scoring/ranking, 7. performing another subjective experiment for validation and further study, 8. Continuing the development for improved colour rendering metric.

Introduction to the study on colour rendering metrics – task 3.1


Test comparison Reference

LED CCT

Set of TCS uniform colour space

__ ΔE |3D vector| (CRV) Gamut (area) (graph from Zukauskas – Colour rendition properties SSL paper)

Fidelity Quality Index Vividness

CIE Daylight 5000 K

Planckian Radiator

Set of TCS

Colour Rendering: Reference-based approach implementation


A review of proposals for colour rendition metrics has been conducted, then the metrics have been sorted and implemented.

• Reference source based methods – magnitude of colour distortion between target

and reference (daylight, Planckian radiator) of same CCT and on a set of TCS : • Fidelity based methods ( CRI, CRI-CAMUCS update of CRI, RCRI ranking ) • Non-fidelity based methods ( CQS : discounts positive chroma shift) • Gamut based methods ( GAI, GAS, FCI with luminance) – to supplement CRI, CQS –

combined metric - [absolute/relative gamut] • Statistical methods : colour categories CCRI, CRV map, multidimensional criterion on

fidelity, saturation , hue (counts on CRV tolerance) • Specific attribute based methods : colour harmony (HRI) / colour categories CCIR

• Non reference source based methods : • Memory colours : similarity functions of memory colour objects (MCRI) • Miscellaneous : fidelity based but with modified TCS for reference (Flattery index)

Review and implementation of proposals for a new metric


Review of proposals for a new metric : results on 122 SPDs Application of the reviewed metrics on a set of 122 spectra of light sources representing all technologies.

SPD categories

0 7 14 21 28 35 42 49 56 63 70 77 84 91 98 105 112 119SPD N°

QTH/incandescent Fluorescent HMI/Hg/Xe HPS LED clusters LED PC LED PC NUV

Comparison CIE Ra 13.3 / MCRI

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SPD N°

Value

CIE Ra 13.3

MCRI


Review of proposals for a new metric : results on 122 SPDs

Pearson correlation coefficients between metrics for the LED sources are quite low in comparison to those obtained with fluorescent sources demonstrating the special dimension of LED lighting

Pearson correlation between metrics(mean of correlations of one metric with the others)

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Ra

Ra9

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CAM xy

CAM +R

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CIE CIE CQS CRI RCRIMCRI CFI CCRI HRI CFI GAI GAS FCI 2*HRI

CorrelationCoefficient

Fluorescent sources (52 SPDs)

LED sources (49 SPDs)


Attributes to be judged with proposed definition and on 5 point-scale

Global preference (observer’s own criterion) Fidelity of colours (feeling of “true – false” colours) Quality of vividness (like – dislike) Naturalness: global, foliage, fruits/vegetables, skin (perceived degree of

naturalness)

Quality of the colour chart (colour discrimination, saturation, shading,…)

43 Panellists: from 20 to 61 years old, 29 males / 14 females

Panellist's data

The colour subjective experiment Objective of the experiment To obtain from a panel of naïve observers the rating of global preference and detailed quality attributes - without reference lighting source - in a common environment and with all the common lighting technologies (QTH, FL tube, CFL, LED cluster, LED Phosphor-Converted (blue/NUV LED).


Subjective experiment : test room

Light panel : lamps behind a diffuser and attached to 3 frames


Subjective experiment : LED SPDs

00.10.20.30.40.50.60.70.80.9

1

380 480 580 680 780Wavelenght (nm)

Spe

ctra

l den

sity

LED WW2700K

LED WR2700K

LEDRGBY2700KLED RGB5000K

LED NUV5000K

LED CW5000K

SPD of 6 LED light sources used in the experiment


Subjective experiment : average ratings of the quality attributes

The result of the PCA is that all attributes are represented with the first principal component ”factor 1” at a level of 66 % (total variability) and in the same direction.

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FL 5000k LED NUV5000k

LED CW5000k

LED RGB5000k

LED WR2700K

CFL2700K

LEDRGBY2700K

HAL2700K

LED WW2700K

Global preference

Fidelity

Quality of vividness

Naturalness

Chart quality


Comparison of predictions with subjective preference

Linear scaling of average observers scores

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FL5000K

LEDNUV

5000K

LED CW5000K

LEDRGB

5000K

LED WR2700K

CFL2700K

RGBY2700K

HAL2700K

LED WW2700

CIE Ra

CQS

MCRI

CRICAM-UCS

RCRI

Global preference


Comparison of predictions with subjective preference : correlations The following tables are the Pearson (linear) and Spearman (rank) coefficients of correlation of metrics with the subjective rating of preference – [scores are rounded at +/- 1%].

These results show that there is a difference of metrics correlation between warm light sources and cold light sources. While current CRI Ra fails for warm LEDs, proposals better perform but exhibits lower correlation for cold light sources – Better correlation calculation and more samples by categories are needed to give better statements.

Pearson CIE Ra CQS Qg MCRI CRI CAMUCS RCRIall light sources 0,918 0,778 -0,028 0,868 0,788cold lights 0,997 0,968 -0,022 0,996 0,895warm lights 0,666 0,606 0,136 0,738 0,648all LED sources 0,921 0,847 0,026 0,913 0,829all cold LED 1,000 0,958 -0,236 0,997 0,853all warm LED 0,000 0,500 0,945 0,693 0,693

Spearman CIE Ra CQS Qg MCRI CRI CAMUCS RCRIall light sources 0,616 0,466 -0,112 0,605 0,538cold lights 0,949 0,949 -0,316 0,949 0,943warm lights 0,526 0,289 -0,026 0,359 0,526all LED sources 0,667 0,750 0,074 0,812 0,794all cold LED 1,000 1,000 -0,500 1,000 0,866all warm LED 0,000 0,500 0,866 0,866 0,866


• Differences in dimensions of colour rendering (fidelity, preference), in approach of proposals, in predictions, and in assessments with subjective experiments show that a good deal of work is needed to validate metric and reach consensus.

• one outcome of the experiment is that for low gamut/low quality (low CCT) enhancement such as chroma increase (LED lighting property), is preferred but for higher gamut/quality (high CCT) increase of saturation has no effect or is not desirable. We will propose a metric based on this principle.

• Industries will not adopt a metric not endorsed by CIE, and CIE will not adopt metrics not thoroughly tested by subjective experiments. Among metrics under consideration at CIE TC1-69 there are the CQS and the nCRI - nCRI is based on CRI-CAM02US with a larger set of TCS, selected with regards to low and high colour constancy, and with scaling formulae method similar to CQS.

Assessment of Colour Rendering Metrics: Conclusion


Introduction to the study on visual comfort – Task 3.2

The study has been conducted through the following steps: 1. Performing specialized subjective experiments (2) - 2. Performing subjective experiments in real situations (3) with 50 people 3. Characterising visual fields (spectro-radiometers, goniometric photometric

camera) 4. Modelling and combining influent parameters

There is no model of visual comfort, the following parameters are usually considered : Glare : the only existing metric (CIE UGR for interior lighting) Light distribution ( luminance, illuminance levels and distributions) Spectral content ( CCT, colour rendition properties) Flicker (not addressed in this task)


Illustrative pictures of the 5 subjective experiments for visual comfort

4 compartments

Living room 4 conf. 2 positions

office 4 conf.

Direct glare 5 conf.

Pupil size set up 3 sources


Visual Comfort: A model ?

Visual comfort is not only glare but too much glare = no comfort regardless other characteristics 1/ Glare UGR normal/small source

2/ Lighting utility: Aesthetical effect ease of Task

(Level, distribution, colour properties)

Ratio between working plane/background

3/ Appearance of luminaires

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imperceptible perceptible

acceptable uncomfortable

intolerable glare

other parametersweighting function

Glare weightingfunction

Not glare dependant

Too strong Glare: No comfort

Glare dependant

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Relative Luminance Level

level of comfort

Too dark

Too bright

Office : enough light but not too much on working plane

Office : uniformity of working plane

Fidelity/ naturalness (CRI-CAMUCS) – vividness (gamut GAI)

Distribution on the area around the luminaire

4/ Spectral effect Not in the model


Calculation on high definition polar Luminance Maps 120°(V)x 135°(H) - array of 4096 x 4096 floats.

Luminance maps are reconstructed from 72 pictures acquired with the photometric camera, mounted on a goniometric platform, with 3 integration times and 3 optical densities (648 images).

Images of luminance maps with a log scale


Comparison of rating of glare sensation and CIE UGR formula: normal and small source

led LED Spot Bare LED Halogen LED Diffuse LED Tubecm² 2.05 1.45 1.92 19.95 11.05

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LED Spot Bare LED Halogen LED Diffuse LED Tube0

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UGR small source

Subjective Glare

Note on CIE glare formula : luminance of small source = luminance of a 50 cm² source of the same intensity.

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Average of UGR normal

Subjective Glare


Graphs of subjective experiments results with LED and traditional light

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A (HL + FL) B (CFL + FL) C (LED spot) D (LED diffuse)

ComfortVisual ClarityEase to writingGeneral averageAverage of ranking

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Halogen Warm LED Neutral LED COLD LED

Comfort Visual ClarityQuality of Documents General averageAverage of ranking

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LED Diffuse n°1 LED Spot LED Diffuse n°2 Halogen

comfort glare color rendering similarity

Living room : LED spot best Compartments : halogen – neutral LED best

Office subjective ratings : CFL best Pupil size decreases with CCT


Visual comfort : First Model Results

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Halogen Warm LED Neutral LED cold LED9.2

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calculated comfort

subjecitve comfort

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CFL + TubeFL

Spot LED +tube LED

LED diffuse +tube LED

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subjecitve comfort

calculated comfort

Office Living Room

Compartments

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LED Diffuse n°1 Led Spot LED Diffuse n°2 Halogen0

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subjecitve comfortcalcuted comfort


Introduction to the study on mesopic vision – Task 3.3 Mesopic system: bridges the gap between CIE Photopic and scotopic

observer functions Because no/few results on mesopic measurements/devices were available

before ENG05, standards are not considering the mesopic conditions. ENG05 results will be used for standardisation BUT spectrum knowledge and angular distribution will be necessary to improve

design calculations


Contribution to standard activities – mesopic vision

Sources can be identified by S/P ratio : S/P = Scotopic output / Photopic output

High values improves mesopic performance The spectra emitted by SSL luminaires change with the angular direction

of emission, so the ratio photopic/mesopic luminous intensity is not constant with direction.

As a consequence, a road lighting installation designed considering photopic quantities could not satisfy uniformity and average requirements when measured in mesopic conditions.

Field trials on SSL-based street and tunnel lightings have been

performed with the detectors developed in WP1. Measurement procedures for mesopic characterisation of SSL of

street lighting luminaires are the output of this task.


Thank you for your attention !