Color vision enables us to discriminate objects based on the wavelength composition of reflected light, but this is not all about the functional contributions of color to visual recognition. Since a trichromatic image carries more information about the optical properties of a scene than a monochromatic image does, color could help us recognize complex material qualities. For instance, color vision assists our gloss perception. For glossy dielectric materials, the spectral distribution of illumination is preserved in the specular reflection, while modulated by surface light absorption for the diffuse reflection. When this physical constraint holds (e.g., red highlights on red body, white highlights on red body), human observers perceive naturalistic glossy surfaces. However, when the constraint is violated (e.g., red highlights on white body, red highlights on green body), the highlights look unnatural (Nishida et al., VSS 2008, 2011). We also found that human vision uses color statistics of an image for the perception of an ecologically important surface condition, i.e., wetness (Sawayama, Adelson & Nishida, 2017, Journal of Vision). Psychophysical experiments showed that overall enhancement of chromatic saturation, combined with a luminance tone change that increases the darkness and glossiness of the image, tends to effectively make dry scenes look wetter. Theoretical analysis along with image analysis of real objects indicated that our image transformation, which we call the wetness enhancing transformation (WET), is consistent with actual optical changes produced by surface wetting.
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