The ability of color-deficient observers to discriminate between illuminant changes and surface-reflectance changes in a scene was tested with natural and Munsell reflectance spectra. To avoid the confounding effects of spatial structure, stimuli were simulations of Mondrian-like colored patterns, presented on a computer-controlled color monitor. Protanopes performed less well than normal trichromats, regardless of the type of reflectance spectra, but they were least disadvantaged with patterns comprising reflectance spectra drawn from urban and rural scenes, more characteristic of the natural environment.

Relational color constancy refers to the constancy of the perceived relations between the colors of surfaces of a scene under changes in the spectral composition of the illuminant. Spatial ratios of cone excitations provide a natural physical basis for this constancy, as, on average, they are almost invariant under illuminant changes for large collections of natural surfaces and illuminants. The aim of the present work was to determine, computationally, for specific surfaces and illuminants, the constancy limits obtained by the application of a minimum-variance principle to cone-excitation ratios and to investigate its validity in predicting observers' surface-color judgments. Cone excitations and their changes due to variations in the color of the illuminant were estimated for colored surfaces in simulated two-dimensional scenes of colored papers and real three-dimensional scenes of solid colored objects. For various test surfaces, scenes, and illuminants, the estimated levels of relational color constancy mediated by cone-excitation ratios varied significantly with the test surface and only with certain desaturated surfaces corresponded to ideal matches. Observers' experimental matches were compared with predictions expressed in CIE 1976 (u′,v′) space and were found to be generally consistent with minimum-variance predictions.