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Alan L. Gilchrist; Disentangling object color from illuminant color: The role of gradient correlations. Journal of Vision 2004;4(8):160. doi: https://doi.org/10.1167/4.8.160.
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Theories of color constancy have traditionally sought to explain surface color perception by suppressing the illuminant-color component of the image. Theories of color vision have been generally concerned with front-end encoding problems, to the neglect of surface color in complex scenes. However, information for disentangling surface and illuminant color exists in the form of gradient correlations. Gilchrist and Ramachandran (1992) showed that the negative correlation between saturation and intensity is used to distinguish a red room in white light from a white room in red light. But colored light added to a scene containing additional ambient light can be distinguished by a positive saturation/intensity correlation. We tested the effectiveness of these gradient correlations in a series of experiments. In one experiment, observers viewed colored cylinders illuminated by colored light in the otherwise dark environment of a vision tunnel. Matches for both perceived surface color and perceived illuminant color were made from an electronic Munsell color book presented on a laptop computer. Identification of both surface and illuminant color was excellent. In a second, more reduced experiment, observers viewed disks on a CRT screen. Each disk was covered with a color/luminance gradient extending from high luminance of one color to low luminance of another color, producing the appearance of a colored sphere illuminated with colored light. The matches showed that the color of the high end was attributed to the illuminant while the color of the low end was attributed to the surface. Additional field experiments were conducted in nighttime urban settings, using buildings illuminated by colored light as stimuli. We conclude that (A) humans perceive the color of the illuminant in addition to the color of the surface, and (B) surface and illuminant colors are distinguished using correlations in the image between color and intensity gradients.
National Science Foundation: BCS-0236701 Public Health Service: GM 60826-02
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