A unified account of gloss and lightness perception in terms of gamut relativity

Abstract

A recently introduced computational theory of visual surface representation, termed gamut relativity, overturns the classical assumption that brightness, lightness, and transparency constitute perceptual dimensions corresponding to the physical dimensions of luminance, diffuse reflectance, and transmittance, respectively. Here I extend the theory to show how surface gloss and lightness can be understood in a unified manner in terms of the vector computation of "layered representations" of surface and illumination properties, rather than as perceptual dimensions corresponding to diffuse and specular reflectance, respectively. The theory simulates the effects of image histogram skewness on surface gloss/lightness and lightness constancy as a function of specular highlight intensity. More generally, gamut relativity clarifies, unifies, and generalizes a wide body of previous theoretical and experimental work aimed at understanding how the visual system parses the retinal image into layered representations of surface and illumination properties.

A Unified Account of Perceptual Layering and Surface Appearance in Terms of Gamut Relativity

“…The horizontal vector depicts the shift of points from standard to comparison gamuts, which compensates for the presumptive illumination difference between sets and . Figure modified with permission from [56] .…”

“…This observation has proven difficult to explain in terms of classical transparency models [6] . Gamut relativity has also been extended to the domain of specularly reflecting surfaces to provide a unified account of layered perceptual representation in lightness and gloss perception [56] .…”

Toward the soft metrology of surface gloss: A review

“…The model can however only be used for images represented on a standard dynamic range display, under the assumption that the diffuse reflectance is spatially uniform over the entire image. 107 It is furthermore assumed that the mode (most frequent) luminance value results from a diffusely reflecting surface component under ambient illumination (the surface lightness layer); variations in luminance must then be due either to specular reflections (higher luminance values) or to shading=shadowing (lower luminance values). By mapping all luminance values to whiteness and blackness coordinates, the entire image can be parsed into a surface lightness layer and illumination layers (corresponding to highlight and to shading=shadowing regions, resp.)…”

Brightness scaling according to gamut relativity

“…Gamut relativity further proposes that the perceptual dimensions composing two-dimensional achromatic color space 9,10 are "whiteness" and "blackness," [2][3][4]9,11,12 and that these dimensions support brightness, lightness, transparency, and gloss perception (see Ref. 13). [2][3][4] In gamut relativity, it is assumed that brightness magnitude estimation involves a comparison between target achromatic color and a background-dependent "reference black" represented on the blackness axis in blackness-whiteness space.…”

“…This definition requires that one relinquish the classical idea of "absolute black and white," 2 replacing it with the more general formulation of gamut relativity, which is consistent with a wide range of otherwise puzzling perceptual phenomena in visual surface perception (see Ref. 13). 3,4 According to the definition provided in, 2 the brightness difference between a pair of target regions is a function of the exponentiated vector magnitude between points in blackness-whiteness space.…”