Evaluation of linear models of surface spectral reflectance with small numbers of parameters

Journal of the Optical Society of America. A, Optics and Image Science
L T Maloney

Abstract

Recent computational models of color vision demonstrate that it is possible to achieve exact color constancy over a limited range of lights and surfaces described by linear models. The success of these computational models hinges on whether any sizable range of surface spectral reflectances can be described by a linear model with about three parameters. In the first part of this paper, I analyze two large sets of empirical surface spectral reflectances and examine three conjectures concerning constraints on surface reflectance: that empirical surface reflectances fall within a linear model with a small number of parameters, that empirical surface reflectances fall within a linear model composed of band-limited functions with a small number of parameters, and that the shape of the spectral-sensitivity curves of human vision enhance the fit between empirical surface reflectances and a linear model. I conclude that the first and second conjectures hold for the two sets of spectral reflectances analyzed but that the number of parameters required to model the spectral reflectances is five to seven, not three. A reanalysis of the empirical data that takes human visual sensitivity into account gives more promising results. The linear ...Continue Reading

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