Abstract
The average color in a scene is a potentially important cue to the illuminant and thus for color constancy, but it remains unknown how well and in what ways observers can estimate the mean chromaticity. We examined this by measuring the variability in “achromatic” settings for stimuli composed of different distributions of colors. The displays consisted of a 15 by 15 palette of colors shown on a gray background on a monitor, with each chip subtending 0.5 deg. Individual colors were randomly sampled from varying contrast ranges along the luminance, S and LM cardinal axes. Observers were instructed to adjust the chromaticity of the palette so that the mean was gray, with variability estimated from 20 or more repeated settings. This variability increased progressively with increasing contrast in the distributions, with large increases for chromatic contrast but also weak effects for added luminance contrast. Signals along the cardinal axes are relatively independent in many detection and discrimination tasks, but showed strong interference in the white estimates. Specifically, adding S contrast increased variability in the white settings along both the S and LM axes, and vice versa. This “cross-masking” and the effects of chromatic variance in general may occur because observers cannot explicitly perceive or represent the mean of a set of qualitatively different hues (e.g. that red and green hues average to gray), and thus may infer the mean only indirectly (e.g. from the relative saturation of different hues).
Meeting abstract presented at VSS 2015