For some sets of surfaces, the spatial ratios of cone-photoreceptor excitations produced by light reflected from pairs of surfaces are almost invariant under illuminant changes. These sets include large populations of spectral reflectances, some of which represent individual natural surfaces but not their relative abundances in nature. The aim of this study was to determine whether spatial cone-excitation ratios are preserved under illuminant changes within the natural visual environment. A fast hyperspectral imaging system was used to obtain populations of 640,000 reflectance spectra from each of 30 natural scenes. The statistics of spatial cone-excitation ratios for randomly selected pairs of points in these scenes were determined for two extreme daylights. Almost-invariant ratios were common, suggesting that they represent a reliable property of the natural visual environment and a suitable foundation for visual color constancy.

Estimates of the frequency of metameric surfaces, which appear the same to the eye under one illuminant but different under another, were obtained from 50 hyperspectral images of natural scenes. The degree of metamerism was specified with respect to a color-difference measure after allowing for full chromatic adaptation. The relative frequency of metameric pairs of surfaces, expressed as a proportion of all pairs of surfaces in a scene, was very low. Depending on the criterion degree of metamerism, it ranged from about 10(-6) to 10(-4) for the largest illuminant change tested, which was from a daylight of correlated color temperature 25,000 K to one of 4000 K. But, given pairs of surfaces that were indistinguishable under one of these illuminants, the conditional relative frequency of metamerism was much higher, from about 10(-2) to 10(-1), sufficiently large to affect visual inferences about material identity.

The number of colors discernible by normal trichromats has been estimated for the idealized object-color solid. How well these estimates apply to natural scenes is an open question, as it is unknown how much their colors approach the theoretical limits. The aim of this work was to estimate the number of discernible colors based on a database of hyperspectral images of 50 natural scenes. The color volume of each scene was computed in the CIELAB color space and was analyzed using the CIEDE2000 color-difference formula. It was found that the color volume of the set of natural scenes was about 30% of the theoretical maximum for the full object-color solid, and it corresponded to a number of about 2.3 million discernible colors. Moreover, when the lightness dimension was ignored, only about 26,000 (1%) could be perceived as different colors. These results suggest that natural stimuli may be more constrained than expected from the analysis of the theoretical limits.

If surfaces in a scene are to be distinguished by their color, their neural representation at some level should ideally vary little with the color of the illumination. Four possible neural codes were considered: von-Kries-scaled cone responses from single points in a scene, spatial ratios of cone responses produced by light reflected from pairs of points, and these quantities obtained with sharpened (opponent-cone) responses. The effectiveness of these codes in identifying surfaces was quantified by information-theoretic measures. Data were drawn from a sample of 25 rural and urban scenes imaged with a hyperspectral camera, which provided estimates of surface reflectance at 10-nm intervals at each of 1344 x 1024 pixels for each scene. In computer simulations, scenes were illuminated separately by daylights of correlated color temperatures 4000 K, 6500 K, and 25,000 K. Points were sampled randomly in each scene and identified according to each of the codes. It was found that the maximum information preserved under illuminant changes varied with the code, but for a particular code it was remarkably stable across the different scenes. The standard deviation over the 25 scenes was, on average, approximately 1 bit, suggesting that the neural coding of surface color can be optimized independent of location for any particular range of illuminants.

No abstract

Quantitative measurements of perceptual colour constancy show that human observers have a limited and variable ability to match coloured surfaces in scenes illuminated by different light sources. Observers can, however, make fast and reliable discriminations between changes in illuminant and changes in the reflecting properties of scenes, a discriminative ability that might be based on a visual coding of spatial colour relations. This coding could be provided by the ratios of cone-photoreceptor excitations produced by light from different surfaces: for a large class of pigmented surfaces and for surfaces with random spectral reflectances, these ratios are statistically almost invariant under changes in illumination by light from the sun and sky or from a planckian radiator. Cone-excitation ratios offer a possible, although not necessarily unique, basis for perceptual colour constancy in so far as it concerns colour relations.

SUMMARYRatios of excitations in each cone-photoreceptor class produced by light reflected from pairs of surfaces in a scene are almost invariant under natural illuminant changes. The stability of these spatially defined ratios may explain the remarkable ability of human observers to efficiently discriminate illuminant changes from changes in surface reflectances. Spatial cone-excitation ratios are not, however, exactly invariant. This study is concerned with observers' sensitivity to these invariance violations. Simulations of Mondrian paintings with either 49 or two natural surfaces under Planckian illuminants were presented as images on a computer-controlled display in a two-interval experimental design: in one interval, the surfaces underwent an illuminant change; in the other interval, the surfaces underwent the same change but the images were then corrected so that, for each cone class, ratios of excitations were preserved exactly. Although the intervals with corrected images corresponded individually to highly improbable natural events, observers systematically misidentified them as containing the illuminant changes, the probability of error increasing as the violation of invariance in the other interval increased. For the range of illuminants and surfaces tested, sensitivity to violations of invariance was found to depend on cone class: it was greatest for long-wavelength-sensitive cones and least for short-wavelength-sensitive cones. Spatial cone-excitation ratios, or some closely related quantities, seem to be the cues preferred by observers for making inferences about surface illuminant changes.

Estimates of the frequency of metameric surfaces, which appear the same to the eye under one illuminant but different under another, were obtained from 50 hyperspectral images of natural scenes. The degree of metamerism was specified with respect to a color-difference measure after allowing for full chromatic adaptation. The relative frequency of metameric pairs of surfaces, expressed as a proportion of all pairs of surfaces in a scene, was very low. Depending on the criterion degree of metamerism, it ranged from about 10 −6 to 10 −4 for the largest illuminant change tested, which was from a daylight of correlated color temperature 25,000 K to one of 4000 K. But, given pairs of surfaces that were indistinguishable under one of these illuminants, the conditional relative frequency of metamerism was much higher, from about 10 −2 to 10 −1 , sufficiently large to affect visual inferences about material identity.