Color constancy based on the geometry of color distribution

Abstract

A white surface appears white under different lighting environments. This ability is referred to color constancy. The physical inputs to our visual system are dictated by the interplay between lights and surfaces, and thus for the surface color to be stably perceived, the illuminant influence needs to be discounted. To reveal our strategy to infer the illuminant color, we conducted three psychophysical experiments designed to test optimal color hypothesis: we internalize the physical color gamut under a particular illuminant and apply the prior to estimate the illuminant color. In each experiment, we presented 61 hexagons arranged without spatial gaps, where the surrounding 60 hexagons were set to have a specific shape in their color distribution. We asked participants to adjust the color of a center test field so that it appears a full-white surface placed under a test illuminant. Results and computational modeling suggested that although our proposed model is limited in accounting for estimation of illuminant intensity by human observers, it agrees fairly well with the estimates of illuminant chromaticity in most tested conditions. The accuracy of estimation generally outperformed other tested conventional color constancy models. These results support the hypothesis that our visual system can utilize the geometry of scene color distribution to achieve color constancy.