Color constancy in natural scenes explained by global image statistics

Abstract

To what extent do observers' judgments of surface color with natural scenes depend on global image statistics? To address this question, a psychophysical experiment was performed in which images of natural scenes under two successive daylights were presented on a computer-controlled high-resolution color monitor. Observers reported whether there was a change in reflectance of a test surface in the scene. The scenes were obtained with a hyperspectral imaging system and included variously trees, shrubs, grasses, ferns, flowers, rocks, and buildings. Discrimination performance, quantified on a scale of 0 to 1 with a color-constancy index, varied from 0.69 to 0.97 over 21 scenes and two illuminant changes, from a correlated color temperature of 25,000 K to 6700 K and from 4000 K to 6700 K. The best account of these effects was provided by receptor-based rather than colorimetric properties of the images. Thus, in a linear regression, 43% of the variance in constancy index was explained by the log of the mean relative deviation in spatial cone-excitation ratios evaluated globally across the two images of a scene. A further 20% was explained by including the mean chroma of the first image and its difference from that of the second image and a further 7% by the mean difference in hue. Together, all four global color properties accounted for 70% of the variance and provided a good fit to the effects of scene and of illuminant change on color constancy, and, additionally, of changing test-surface position. By contrast, a spatial-frequency analysis of the images showed that the gradient of the luminance amplitude spectrum accounted for only 5% of the variance.

Figure 1

Example scenes and corresponding plots of surface-color judgments. The images A–H subtended approx. 17° × 14° visual angle in the experiment and each contained a test surface, either a small sphere (A–G) or part of a building (H), indicated by arrows. In the corresponding contour plots a–h, the relative frequency of observers' “illuminant-change” responses to a change in illuminant on the scene and variable test-surface reflectance is shown in the CIE 1976 (u′, v′) chromaticity diagram as a function of the chromaticity of the reflectance change: the darker the contour, the higher the frequency. The square symbols show the position of the first illuminant (daylight with correlated color temperature 25,000 K in a–d, 4000 K in e–h); the circles the second illuminant (6700 K); and the triangles the mode (and where large enough the bars show ±1 SE), from which the color-constancy index was derived. With perfect constancy, the triangles and circles are coincident. The line marked L is the daylight locus.

Figure 2

Examples of illuminant and reflectance changes for detail of scene F of Fig. 1. A and B: a gray sphere in scene under daylight of correlated color temperature 25,000 K and 6700 K, respectively; C and D, a reddish sphere in scene under the same two illuminants. The sequences A to B and C to D both illustrate illuminant changes; the sequence A to D illustrates an illuminant change with a reflectance change.

Figure 3

Variation of surface-color judgments. Color-constancy index is plotted against the log of the mean relative deviation in spatial cone-excitation ratios for each scene under two illuminants. Filled squares are for 21 scenes with first illuminant a daylight with correlated color temperature 25,000 K and second illuminant 6700 K (data from 12 observers); filled circles are for 18 scenes with first illuminant 4000 K and second illuminant 6700 K (data from 7–8 observers); open circles are for images in the quartile with the highest mean chroma under the first illuminant or highest difference in mean chroma. The dotted line is an unweighted linear regression.