A quarter of a century ago, the first systematic behavioral experiments were performed to clarify the nature of color constancy-the effect whereby the perceived color of a surface remains constant despite changes in the spectrum of the illumination. At about the same time, new models of color constancy appeared, along with physiological data on cortical mechanisms and photographic colorimetric measurements of natural scenes. Since then, as this review shows, there have been many advances. The theoretical requirements for constancy have been better delineated and the range of experimental techniques has been greatly expanded; novel invariant properties of images and a variety of neural mechanisms have been identified; and increasing recognition has been given to the relevance of natural surfaces and scenes as laboratory stimuli. Even so, there remain many theoretical and experimental challenges, not least to develop an account of color constancy that goes beyond deterministic and relatively simple laboratory stimuli and instead deals with the intrinsically variable nature of surfaces and illuminations present in the natural world.

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.

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.

Tritan color-vision deficiency is an autosomal dominant disorder associated with mutations in the short-wavelength-sensitive- (S-) cone-pigment gene. An unexplained feature of the disorder is that individuals with the same mutation manifest different degrees of deficiency. To date, it has not been possible to examine whether any loss of S-cone function is accompanied by physical disruption in the cone mosaic. Two related tritan subjects with the same novel mutation in their S-cone-opsin gene, but different degrees of deficiency, were examined. Adaptive optics was used to obtain high-resolution retinal images, which revealed distinctly different S-cone mosaics consistent with their discrepant phenotypes. In addition, a significant disruption in the regularity of the overall cone mosaic was observed in the subject completely lacking S-cone function. These results taken together with other recent findings from molecular genetics indicate that, with rare exceptions, tritan deficiency is progressive in nature.