Color appearance: effects of illuminant changes under different surface collections.

A theory about how changes in the illuminant affect the color appearance of objects must specify how the visual system's adjustments to illuminant changes vary with the surface collection in a scene. I report an experiment designed to investigate this issue. The stimuli were CRT simulations of flat matte surfaces rendered under diffuse illumination. For all combinations of 7 daylight illuminants and 12 collections of surface reflectances the subject's achromatic locus was measured on an isoluminant plane in color space. For any surface collection the changes in the achromatic locus could be well approximated by a linear transformation of the illuminant changes. These linear transformations showed relatively small variation with the surface collection. To first approximation, these results suggest that the effect of changes in the illuminant on color appearance can be described linearly and that it can be separated from the surface collection. There was an effect of the surface collection on the achromatic locus. The data rejected the idea that a surface collection's mean reflectance function might capture this effect, ruling out models of color appearance that are based on this kind of averaging assumption.

[1]  S. S. Wilks.  CERTAIN GENERALIZATIONS IN THE ANALYSIS OF VARIANCE , 1932 .

[2]  K. S. Gibson,et al.  Tristimulus Specification of the Munsell Book of Color from Spectrophotometric Measurements , 1943 .

[3]  W. R. Brown,et al.  Statistics of Color-Matching Data* , 1952 .

[4]  Robert W. Burnham,et al.  Prediction of Color Appearance with Different Adaptation Illuminations , 1957 .

[5]  T. W. Anderson,et al.  An Introduction to Multivariate Statistical Analysis , 1959 .

[6]  T. W. Anderson.  An Introduction to Multivariate Statistical Analysis , 1959 .

[7]  H. Condit,et al.  Spectral Energy Distribution of Daylight , 1964 .

[8]  D. B. Judd,et al.  Spectral Distribution of Typical Daylight as a Function of Correlated Color Temperature , 1964 .

[9]  J. Cohen.  Dependency of the spectral reflectance curves of the Munsell color chips , 1964 .

[10]  D. Krantz.  A theory of context effects based on cross-context matching , 1968 .

[11]  C. M. Cicerone,et al.  Opponent-process additivity--I: red-green equilibria. , 1974, Vision research.

[12]  D. Krantz.  Color measurement and color theory: II. Opponent-colors theory , 1975 .

[13]  David H. Krantz,et al.  Opponent-process additivity—III Effect of moderate chromatic adaptation , 1975, Vision Research.

[14]  David H. Krantz,et al.  Opponent process additivity—II. Yellow/blue equilibria and nonlinear models , 1975, Vision Research.

[15]  J. Walraven.  Discounting the background—the missing link in the explanation of chromatic induction , 1976, Vision Research.

[16]  S. Shevell.  The dual role of chromatic backgrounds in color perception , 1978, Vision Research.

[17]  G. Buchsbaum.  A spatial processor model for object colour perception , 1980 .

[18]  D. W. Heeley,et al.  Cardinal directions of color space , 1982, Vision Research.

[19]  J. Werner,et al.  Effect of chromatic adaptation on the achromatic locus: The role of contrast, luminance and background color , 1982, Vision Research.

[20]  L. Arend,et al.  Simultaneous color constancy. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[21]  J. Schmee.  An Introduction to Multivariate Statistical Analysis , 1986 .

[22]  L. Maloney.  Evaluation of linear models of surface spectral reflectance with small numbers of parameters. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[23]  L. Maloney,et al.  Color constancy: a method for recovering surface spectral reflectance , 1987 .

[24]  R. Hunt,et al.  A model of colour vision for predicting colour appearance in various viewing conditions , 1987 .

[25]  The spectral energy distribution of the scattered light from dark clouds , 1989 .

[26]  M. Landy,et al.  A Bilinear Model of the Illuminant's Effect on Color Appearance , 1991 .

[27]  K. Gegenfurtner.  PRAXIS: Brent’s algorithm for function minimization , 1992 .

[28]  B. Wandell,et al.  Asymmetric color matching: how color appearance depends on the illuminant. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[29]  J. Krauskopf,et al.  Color discrimination and adaptation , 1992, Vision Research.

[30]  M. Lucassen,et al.  Quantifying color constancy: Evidence for nonlinear processing of cone-specific contrast , 1993, Vision Research.

[31]  K. Bäuml.  A ratio principle for a red/green and a yellow/blue channel? , 1993, Perception & psychophysics.