Lightness&&

Ming Huan LeeFeb. 3, 2003

Brightness

CPSC 533CInformation Visualization

Contrast Constancy

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Quantity of Light Luminance

“the measured amount of light coming from some region of space”

Brightness“the perceived amount of light coming from a source” (self-luminous)

Lightness“the perceived reflectance of a surface”

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Merriam-Webster Luminance

“the luminous intensity of a surface in a given direction per unit of projected area”

Brightness“the attribute of light-source colours by which emitted light is ordered continuously from light to dark in correlation with its intensity”

Lightness“the attribute of object colours by which the object appears to reflect or transmit more or less of the incident light”

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Agenda Eyes: Receptive Fields & “DOG” Model Simultaneous Contrast & Errors in

Reading Maps & in Computer Graphics Lightness Constancy: Adaptation &

Contrast Computer Monitor Conclusion

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Our Eyes light-sensing receptors

no info about amount of light (light meter) signal of “differences” (contrast mechanism)

relative amount of light (change meter) differ from neighbouring / change in the past instant

nonlinear, no absolute values (but not inaccurate) reflectance of surfaces

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Human Vision perceive objects from surface

properties, not from the quality and quantity of illumination lightness is unaffected by illumination

lightness constancy

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Receptive Fields the receptive field of a cell is the visual area

over which a cell responds to light stimulate receptive field

on-centre: emits pulses at a greater rate off-centre: emits pulses at a lower rate (inhibited)

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“DOG” Model Difference of Gaussians (DOG)

the firing rate of the cell is the difference between two Gaussians (centre and surround)

DOG receptive field explain a variety of brightness contrast effects Hermann Grid: more inhibition between squares,

hence brighter at the intersections

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Simultaneous Brightness Contrast

the general effect whereby a grey patch placed on a dark background looks lighter than the same grey patch on a light background

cross-cross&

snake

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Simultaneous Contrast & Errors

contrast effects vs. visualization errors of judgment while reading

quantitative (value) info encoded using gray scale ex. in the worst case, found substantial errors

that averaged 20% of the entire scale

Gravity Map of North Atlantic

large errors can occur when values are read using the key

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Gray Scale no perfect gray scale providing only rough approximations

because the visual field is radically changed by many factors

perceived illumination specular reflection from glossy surfaces local contrast effects

contrast crispening differences are perceived as larger when samples are

similar to the background color

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Computer Graphics computer graphics images (not like real world) consist

of simple luminous light patches much of the detailed (high level) texture and shadow

info (like real world) is missing leads to errors and distortions in info displays consequences of contrast effects

tend to show up the deficiencies in the common shading algorithms used in computer graphics

lead to perception of illusory patterns smooth surfaces displayed using polygons (for simplicity and to

speed up computer graphics rendering process) visual system enhances boundaries at edges of polygons (stand out)

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Lightness Constancy

lightness is unaffected by illumination lightness constancy

two important mechanisms in lightness constancy, which help the visual system to factor out the effects of the amount and color of the illumination adaptation contrast

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Adaptation the role

the changing sensitivity of the receptors and neurons in the eye helps factor out the overall level of illumination

allow visual system to adjust overall sensitivity to the ambient light level

example briefly blinded when coming into a

darkened room out of bright sunlight

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Contrast

the role help to achieve constancy by signalling differences in

light levels, especially at the edge of objects Example

(a) receives more light, however, it reflects about the same amount of light as (b)

simultaneous brightness contrast (a) is lighter relative to its background than (b) is, relative to

its background

medium graywhite

(a) (b)

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Additional Factors although both adaptation and contrast can be

seen as mechanisms that act in service of lightness constancy, they are not sufficient brain must take the direction of illumination and

surface orientation into account in lightness judgements

brain seems to use the lightest object in the scene as a kind of reference white to determine the grey values of all other objects

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Additional Factors (Cont’d)

the ratio of specular and nonspecular reflection in the all-dark world, the ratio is much larger

than in the all-white world

Every point on the black image is brighter than the surroundings. How can we perceive something to be black when it is a bright image?

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Computer Monitor contrast illusions are much worse in CRT

no texture (uniform pattern of pixels and phosphor dots) self-luminous (confound lightness constancy)

the colour and the brightness of the surround of the monitor can be very important in determining how screen objects appear

the adaptation effect produced by room light overall contrast is much reduced where the room

light falls on the display LCD?

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Conclusion nervous system computing difference signals visualization is not good for representing

precise absolute numerical values, but rather for displaying patterns of differences of changes over time, to which the eye and brain are extremely sensitive

contrast effects are severe in computer displays as a consequence of the impoverished nature of those displays, not of any inadequacy of the visual system

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Color Use Guidelines for Data Representation

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Color Schemes make the most of the information visualization

by using perceptual dimensions of color in ways that parallel the logical structures in the data to allow its organization to be readily perceived sequential qualitative and binary diverging spectral two-variable

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Sequential Schemes

suited to ordered data that progress from low to high

lightness to represent ordered data

with light colors for low data values to dark colors for high data values ex. a graphic showing

pollution level

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Qualitative and Binary Schemes

do not magnitude differences between legend classes, and hues are use to create the primary difference between classes

best suited to representing nominal or categorical data ex. government spending for

different departments binary schemes

special case for the two categories

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Diverging Schemes put equal emphasis on

mid-range critical values and extremes at both ends of the data range

the critical class or break in the middle of the legend is emphasized with light colors, and low & high extremes are emphasized with dark colors that have contrasting hues

ex. increases and decreases in acid rain over a given time period

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Spectral and Two-Variable Schemes

spectral (rainbow) often misused as a

sequential scheme with poorly used lightness differences

the most informative use of a spectral scheme is as a diverging scheme

two-variable sequential-sequential sequential-qualitative binary-qualitative binary-diverging sequential-diverging diverging-diverging

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Conclusion matching the organization of the

perceptual dimensions of color (hue, lightness, saturation) to the organization of data being represented is one key to gaining insight from data visualization