Color Appearance ModelsColor Appearance Models

The Nayatani et al. ModelThe Nayatani et al. ModelThe Hunt 91 and 94 ModelThe Hunt 91 and 94 Model

The RLAB ModelThe RLAB Model

Iris Zhao

April 21, 2004

BackgroundBackground Color-appearance terminologyColor-appearance terminology Brightness Vs. lightness Brightness Vs. lightness Colorfulness Vs. ChromaColorfulness Vs. Chroma

Color-appearance phenomenaColor-appearance phenomenaHunt Effect (Colorfulness increase with luminance) Hunt Effect (Colorfulness increase with luminance) Stevens Effect (Contrast increase with luminance)Stevens Effect (Contrast increase with luminance)

Helson-Judd Effect (hue of nonselective samples)Helson-Judd Effect (hue of nonselective samples) Helmholtz-Kohlrausch Effect (Brightness depends on luminance Helmholtz-Kohlrausch Effect (Brightness depends on luminance

and chromaticity)and chromaticity) Bezold-BrBezold-Brϋϋcke hue shiftcke hue shift

Chromatic adaptation and chromatic-adaptation modelsChromatic adaptation and chromatic-adaptation models von Kries Model von Kries Model Nayatani’s Model Nayatani’s Model Fairchild’s Model Fairchild’s Model

Color-appearance model and Color-appearance model and chromatic-adaptation transformchromatic-adaptation transform

Y. Nayatani, etcY. Nayatani, etc

The The Nayatani et al. ModelNayatani et al. Model

OutlineOutline

Extension of a nonlinear color-appearance Extension of a nonlinear color-appearance model to white and light-gray background.model to white and light-gray background.

Two chromatic-adaptation transforms : Two chromatic-adaptation transforms : lightness-chroma (Q-C) transform and lightness-chroma (Q-C) transform and brightness-colorfulness (B-M) transform.brightness-colorfulness (B-M) transform.

The usefulness of a combination of a color-The usefulness of a combination of a color-appearance model and its corresponding appearance model and its corresponding chromatic transform.chromatic transform.

The importance of B-M transform.The importance of B-M transform.

Variables Variables The input data for the model include as follows:The input data for the model include as follows: The luminance factor of the background, YThe luminance factor of the background, Y00

Chromaticity coordinates of illuminant, xChromaticity coordinates of illuminant, x00, y, y00

The test stimulus, x, y, YThe test stimulus, x, y, Y

The absolute luminance of the stimulus and adapting field, EThe absolute luminance of the stimulus and adapting field, E00

The normalizing illuminance, EThe normalizing illuminance, Eoror

Cone response for adapting field, Cone response for adapting field, (xi), (xi), (eta) and (eta) and (zeta)(zeta) Cone responses for adapting field in terms of the absolute luminance Cone responses for adapting field in terms of the absolute luminance

level, Rlevel, R00, G, G00, B, B00

Cone responses for the test stimulus, R, G, BCone responses for the test stimulus, R, G, B Opponent-color dimensions, Q, T, POpponent-color dimensions, Q, T, P Brightness for a stimulus and an ideal white, BBrightness for a stimulus and an ideal white, Brr and B and Brwrw

Lightness, L*Lightness, L*PP (L* (L*PP = Q+50) and L* = Q+50) and L*NN (L* (L*NN = 100*B = 100*Brr/B/Brwrw)) Chroma, CChroma, CRGRG, C, CYBYB, C, C Colorfulness, MColorfulness, MRGRG, M, MYBYB, M, M

Prediction of Helson-Judd EffectPrediction of Helson-Judd Effect

Helson-Judd Effect: “Samples lighter than the Helson-Judd Effect: “Samples lighter than the background exhibited chroma of the same hue as background exhibited chroma of the same hue as the source, while samples darker than the the source, while samples darker than the background exhibited chroma of the hue of the background exhibited chroma of the hue of the source’s component.” source’s component.”

The achromatic object colors with Munsell values The achromatic object colors with Munsell values 5/ and 3/ give blueness perception 5/ and 3/ give blueness perception complementary to the hue of illuminant A complementary to the hue of illuminant A (incandescent illuminant); White Background with (incandescent illuminant); White Background with Y0 = 60 (approximately 8/).Y0 = 60 (approximately 8/).

Extension of CIE chromatic-adaptation transformExtension of CIE chromatic-adaptation transform

The limitation of CIE chromatic-adaptation transform: The limitation of CIE chromatic-adaptation transform:

It can be used only when the illuminance of the test field It can be used only when the illuminance of the test field should be the same as that of the reference field in the should be the same as that of the reference field in the condition of a light-gray background; The coefficient A is condition of a light-gray background; The coefficient A is very close to unity. very close to unity.

Or the complex procedure is needed for its computation. Or the complex procedure is needed for its computation. The coefficient A is derived by a complex successive-The coefficient A is derived by a complex successive-approximation method.approximation method.

The computation is simplified by using the nonlinear color-The computation is simplified by using the nonlinear color-appearance model. The analytical form of the coefficient A appearance model. The analytical form of the coefficient A can be obtained.can be obtained.

Two Chromatic-adaptation transformsTwo Chromatic-adaptation transforms

Lightness-chroma match (Q-C transform)Lightness-chroma match (Q-C transform) Brightness-colorfulness match (B-M transform)Brightness-colorfulness match (B-M transform)

The procedure combining of chromatic-adaptation The procedure combining of chromatic-adaptation transforms and color-appearance models is given transforms and color-appearance models is given for each transform. for each transform.

These procedure provide not only colorimetric These procedure provide not only colorimetric values of the corresponding colors (chromatic-values of the corresponding colors (chromatic-adaptation transform) but also the attributes of adaptation transform) but also the attributes of color appearance (color-appearance model). This color appearance (color-appearance model). This is the advantage of combination of these two.is the advantage of combination of these two.

Experiment & ResultsExperiment & Results

Haploscopic matchingHaploscopic matching

The values of lightness and chroma for B-M match The values of lightness and chroma for B-M match are lower than those for Q-C match. (Fig.3)are lower than those for Q-C match. (Fig.3)

The observers can discriminate the difference The observers can discriminate the difference between Q-C and B-M match, because there are between Q-C and B-M match, because there are no overlapping region between those two. (Fig.3)no overlapping region between those two. (Fig.3)

The predicated corresponding colors by Q-C and The predicated corresponding colors by Q-C and B-M transformation are correlated to observed B-M transformation are correlated to observed corresponding colors. (Fig.4 and 5)corresponding colors. (Fig.4 and 5)

ConclusionsConclusions The nonlinear color-appearance model was The nonlinear color-appearance model was

extended to white and light-gray background.extended to white and light-gray background.

The model simplified the complex computations The model simplified the complex computations of the chromatic-adaptation transformation. of the chromatic-adaptation transformation.

Two kinds of chromatic-adaptation transform Two kinds of chromatic-adaptation transform existed. (Q-C and B-M)existed. (Q-C and B-M)

Any color-appearance model should be combined Any color-appearance model should be combined with chromatic-adaptation transformation.with chromatic-adaptation transformation.

Revised Colour-appearance model for Revised Colour-appearance model for related and unrelated coloursrelated and unrelated colours

R. W. G. HuntR. W. G. Hunt

The Hunt 91 modelThe Hunt 91 model

OutlineOutline

Five different visual fields are clearly defined.Five different visual fields are clearly defined. The steps required in the model for both related The steps required in the model for both related

colors and unrelated colors are described. (Refer colors and unrelated colors are described. (Refer to Appendix I and II)to Appendix I and II)

ParametersParameters Results for related colorsResults for related colors Results for unrelated colorsResults for unrelated colors ConclusionsConclusions

ParametersParameters

Cone responses Cone responses , , , , (similar to LMS in the RLAB model) (similar to LMS in the RLAB model)

Cone responses after adaptation Cone responses after adaptation aa, , aa, , a a

Colour difference signal CColour difference signal C11, C, C22, C, C3 3 (dissimilar to CIELAB)(dissimilar to CIELAB)

Hue H, Hue composition HHue H, Hue composition HCC, Hue angle h, Hue angle hSS

Yellowness-blueness, MYellowness-blueness, MYBYB, redness-greenness, M, redness-greenness, MRGRG, and colorfulness M, and colorfulness M

Achromatic signal A: the photopic part AAchromatic signal A: the photopic part Aaa and the scotopic part A and the scotopic part Ass

Saturation s, relative yellowness-blueness, mSaturation s, relative yellowness-blueness, mYBYB, redness-greenness, m, redness-greenness, mRGRG

Brightness Q, lightness JBrightness Q, lightness J

Chroma CChroma Cbb

Whiteness-Blackness QWhiteness-Blackness QWBWB

Verification for Related ColorsVerification for Related Colors

The shape of cone response curves after adaptation, The shape of cone response curves after adaptation, aa, , aa, , a a , is , is reasonable by comparing response curves predicted by the model reasonable by comparing response curves predicted by the model with experimental results. (Fig.6)with experimental results. (Fig.6)

The brightness, Q, gives predictions in very satisfied agreement The brightness, Q, gives predictions in very satisfied agreement with these experimental results. (Fig.7-9)with these experimental results. (Fig.7-9)

The prediction of the hue H, lightness J, chroma CThe prediction of the hue H, lightness J, chroma Cbb, of the model is , of the model is comparable with the interobserver uncertainty.comparable with the interobserver uncertainty.

The model predicts color appearance of special case quite well. The model predicts color appearance of special case quite well. The “famous” picture includes a yellow cushion and a person The “famous” picture includes a yellow cushion and a person wearing a white blouse. (Fig. 10)wearing a white blouse. (Fig. 10)

The increase in the sum of brightness and colorfulness is related The increase in the sum of brightness and colorfulness is related to the increase in luminance. The model predicts the experimental to the increase in luminance. The model predicts the experimental results well.results well.

Unrelated ColorsUnrelated Colors

Although unrelated colors are often seen in completely dark Although unrelated colors are often seen in completely dark fields, the luminance of adapting field is not zero.fields, the luminance of adapting field is not zero.

The chromaticity of adapting field is the same as that of the The chromaticity of adapting field is the same as that of the equi-energy stimulus. equi-energy stimulus.

Unrelated colors are affected by the previous adapting field Unrelated colors are affected by the previous adapting field or the conditional field.or the conditional field.

For unrelated colors, there are no conception of a reference For unrelated colors, there are no conception of a reference white.white.

The luminance level of a stimulus has and effect on its The luminance level of a stimulus has and effect on its apparent hue. This phenomenon is known as the apparent hue. This phenomenon is known as the Bezold-Bezold-BrBrϋϋcke hue shift.cke hue shift.

Verification for Unrelated ColorsVerification for Unrelated Colors

The model predicts Bezold-BrThe model predicts Bezold-Brϋϋcke hue shift, which is cke hue shift, which is correlated with Purdy’s results. (Fig. 12)correlated with Purdy’s results. (Fig. 12)

The model gives the prediction of brightness in satisfactory The model gives the prediction of brightness in satisfactory agreement with Bartleson’s results. (Fig. 13)agreement with Bartleson’s results. (Fig. 13)

The colorfulness of unrelated colors is less than that of The colorfulness of unrelated colors is less than that of related colors seen at the same brightness in the mid-related colors seen at the same brightness in the mid-photopic range. The model predicts the above results, photopic range. The model predicts the above results, similar to that found by Pitt and Winter.similar to that found by Pitt and Winter.

ConclusionsConclusions

The model describes the contributions of the cones and The model describes the contributions of the cones and rods to the achromatic signal, A, appropriately. rods to the achromatic signal, A, appropriately.

For related colors, luminance factor of the background has For related colors, luminance factor of the background has a great effects on the color appearance. a great effects on the color appearance.

For unrelated colors, the model predicts the For unrelated colors, the model predicts the Bezold-BrBezold-Brϋϋcke cke hue shift. hue shift.

An improved Predictor of Colourfulness in An improved Predictor of Colourfulness in a model of colour visiona model of colour vision

R. W. G. HuntR. W. G. Hunt

The Hunt 94 modelThe Hunt 94 model

New Predictor for ChromaNew Predictor for Chroma

For light colors, the new chroma, CFor light colors, the new chroma, C9494, decreases , decreases as the background becomes darker;as the background becomes darker;

For media and dark colors, the new chroma, CFor media and dark colors, the new chroma, C9494, , increases as the background becomes darker;increases as the background becomes darker;

Because the revised model predicts appearance Because the revised model predicts appearance consistently for different viewing condition, the consistently for different viewing condition, the new predictor for Chroma is adopted. new predictor for Chroma is adopted.

The new chroma, CThe new chroma, C9494, describes the effects of , describes the effects of luminous factor of the background more luminous factor of the background more appropriately.appropriately.

New Predictor for ColorfulnessNew Predictor for Colorfulness

The effect of luminance of the adapting field on The effect of luminance of the adapting field on colorfulness is overestimated by the Hunt 91 colorfulness is overestimated by the Hunt 91 model. The power changes from 1/5.5 (0.18) to model. The power changes from 1/5.5 (0.18) to 0.15. 0.15.

New predictor for colorfulness, M94, gives New predictor for colorfulness, M94, gives prediction in agreement with the experimental prediction in agreement with the experimental results. results.

M94 results in a smaller dependence of M94 results in a smaller dependence of colorfulness on adapting luminance, and allows colorfulness on adapting luminance, and allows for the effects of luminance factor of background for the effects of luminance factor of background on the colorfulness. on the colorfulness.

9415.0

94 CFM L

Image color-appearance specification Image color-appearance specification through extension of CIELABthrough extension of CIELAB

Mark D. Fairchild & Roy S. BernsMark D. Fairchild & Roy S. Berns

The RLAB modelThe RLAB model

OutlineOutline

An extension of CIELAB, RLAB, incorporates the An extension of CIELAB, RLAB, incorporates the advantage of CIELAB, a more accurate model of advantage of CIELAB, a more accurate model of chromatic-adaptation and the capability to adjust chromatic-adaptation and the capability to adjust for the changes in surround.for the changes in surround.

RLAB can be used to calculate the attributes of RLAB can be used to calculate the attributes of color appearance. color appearance.

RLAB cab be applied in cross-media reproduction.RLAB cab be applied in cross-media reproduction.

CIELABCIELAB

AdvantagesAdvantages(a) Recommended in 1976;(a) Recommended in 1976;(b) The first approximation to a color-appearance space;(b) The first approximation to a color-appearance space;(c) An adequate color-appearance model at daylight or (c) An adequate color-appearance model at daylight or nearly daylight illumination.nearly daylight illumination.

(d) Take chromatic adaptation into account by normalizing (d) Take chromatic adaptation into account by normalizing tristimulus values XYZ.tristimulus values XYZ.

DisadvantagesDisadvantages(a) Not useful for large changes in viewing conditions.(a) Not useful for large changes in viewing conditions.(b) Less accurate because the normalization performed on (b) Less accurate because the normalization performed on XYZ rather than fundamental tristimulus values LMS. XYZ rather than fundamental tristimulus values LMS. (c) Not account for color-appearance changes due to (c) Not account for color-appearance changes due to changes in illuminant level and surround.changes in illuminant level and surround.

Chromatic-adaptation modelChromatic-adaptation model

The model can predicate the Hunt effect and The model can predicate the Hunt effect and Steven effect, and distinguish the differences Steven effect, and distinguish the differences between reflective (e.g. prints) and self-luminous between reflective (e.g. prints) and self-luminous (e.g. CRT display).(e.g. CRT display).

The model is formulated as a series of matrix The model is formulated as a series of matrix multiplication.multiplication.M: transform matrix from XYZ to LMSM: transform matrix from XYZ to LMS

A: the matrix for chromatic-adaptation transformationA: the matrix for chromatic-adaptation transformation

C: the matrix for calculating post-adaptation signalsC: the matrix for calculating post-adaptation signals

This term is eliminated in the revised model.This term is eliminated in the revised model.

1

1

1

111

21

21

2

2

2

Z

Y

X

MACCAM

Z

Y

X

Effects of SurroundEffects of Surround

A dark surround causes all of the colors to appear lighter. A dark surround causes all of the colors to appear lighter. The effect is larger for darker colors than for lighter colors, The effect is larger for darker colors than for lighter colors, which results a decrease in image contrast.which results a decrease in image contrast.

Several examplesSeveral examples

Cases Gamma Exponents for CIELAB Cases Gamma Exponents for CIELAB

photographic prints viewed in average surround 1.0 1/3photographic prints viewed in average surround 1.0 1/3

projected transparency viewed in dark surround 1.5 1/(3*1.5) = 1/4.5projected transparency viewed in dark surround 1.5 1/(3*1.5) = 1/4.5

CRT display viewed in dim surround 1.25 1/(3*1.25) = 1/3.75CRT display viewed in dim surround 1.25 1/(3*1.25) = 1/3.75

RLABRLAB

R refers to reproduction.R refers to reproduction. Under the reference viewing conditions (CIE illuminant D65, the Under the reference viewing conditions (CIE illuminant D65, the

white luminance 318 cd/mwhite luminance 318 cd/m22, discounting-the-illuminant), the RLAB , discounting-the-illuminant), the RLAB and CIELAB are identical.and CIELAB are identical.

Otherwise, the chromatic-adaptation model is used to convert XYZ Otherwise, the chromatic-adaptation model is used to convert XYZ to the corresponding XYZ under reference viewing conditions. The to the corresponding XYZ under reference viewing conditions. The 1/3 exponents in the CIELAB equation are changed to 1/3.75 for 1/3 exponents in the CIELAB equation are changed to 1/3.75 for

dim surround or 1/4.5 for dark surround.dim surround or 1/4.5 for dark surround.

X Y Z XrefYrefZref

RCAM

LR aR bR CR hR

Exponent 1/3 or 1/3.75 or1/4.5

ER

Model PerformanceModel Performance

The Hunt pillow demonstrationThe Hunt pillow demonstration White shirt Vs. yellow pillowWhite shirt Vs. yellow pillow A experiment was performed to evaluate the A experiment was performed to evaluate the

performance of RLAB space over cross-media performance of RLAB space over cross-media reproduction.reproduction.

X1Y1Z1

X1,refY1,refZ1,ref

ReflectanceDevice colorimetric

characterization

Color-appearance models

Gamut mapping, tone reproduction, etc.

X2Y2Z2

X2,refY2,refZ2,ref

RGB

ConclusionsConclusions

The advantages of RLABThe advantages of RLABIncorporate the advantages of CIELAB;Incorporate the advantages of CIELAB;

Include a more accurate model of chromatic-adaptation;Include a more accurate model of chromatic-adaptation;

Adjust for the changes in surround;Adjust for the changes in surround;

Can be easily invertible.Can be easily invertible.

RLAB can be applied to cross-media RLAB can be applied to cross-media reproduction.reproduction.

Refinement of the RLAB color spaceRefinement of the RLAB color spaceMark D. FairchildMark D. Fairchild

The revised RLAB modelThe revised RLAB model

OutlineOutline

Visual evaluation of RLABVisual evaluation of RLAB Refinement of the RLAB equationsRefinement of the RLAB equations Summary of RLAB equationsSummary of RLAB equations ConclusionsConclusions

Visual evaluation of RLABVisual evaluation of RLAB

Four experiments were performed.Four experiments were performed.print-to-print reproductionprint-to-print reproduction

simple object-color reproductionsimple object-color reproduction

print-to-CRT reproductionprint-to-CRT reproduction

CRT-to-projected slide reproduction CRT-to-projected slide reproduction RLAB performed the best for three experiments except for RLAB performed the best for three experiments except for

the second one. (RLAB performs well for pictorial images the second one. (RLAB performs well for pictorial images and not-so-well for simple patches.)and not-so-well for simple patches.)

The reason is that RLAB introduced unwanted shift in the The reason is that RLAB introduced unwanted shift in the lightness of the samples as the change in luminance level. lightness of the samples as the change in luminance level.

The solution is to remove the C matrix in the revised RLAB The solution is to remove the C matrix in the revised RLAB model.model.

Refinement of the RLAB EquationsRefinement of the RLAB Equations

The C matrix is removed, because it is more The C matrix is removed, because it is more detrimental than beneficial. After that, the model detrimental than beneficial. After that, the model can’t predict the Hunt effect and Stevens effect.can’t predict the Hunt effect and Stevens effect.

The D parameter is added to describe the level of The D parameter is added to describe the level of discounting-the-illuminant, and the model discounting-the-illuminant, and the model becomes more flexible. becomes more flexible.

Power functions are simplified by discarding the Power functions are simplified by discarding the reference white in the standard CIELAB reference white in the standard CIELAB equations.equations.

The M matrix is normalized; The R matrix (MThe M matrix is normalized; The R matrix (M-1-1AA-1-1) ) is also normalized.is also normalized.

ConclusionsConclusions

The revised RLAB performs as well as, or better The revised RLAB performs as well as, or better than more complex color-appearance models, than more complex color-appearance models, e.g. the Hunt model.e.g. the Hunt model.

Two drawbacks of the Hunt model: ambiguity or Two drawbacks of the Hunt model: ambiguity or difficulty in determining so many values in the difficulty in determining so many values in the model; the appearance judgments for images model; the appearance judgments for images depends both on the individual colors, but on the depends both on the individual colors, but on the relationship between colors, e.g. image contrast.relationship between colors, e.g. image contrast.