Matrix R-based Visual Response to Optimal Colors and Application to Image Color Gamut Expansion

Abstract

The optimal colors with maximum chroma at constant lightness present an ideal target for the colorants pursuing the ultimate wide color gamut. MacAdam proved that optimal colors are composed of square pulse-shaped spectra with at least two tansition wavelengths λ1 and λ2 whose reflectances change from 0 to 1 or 1 to 0. The optimal color gamut is created from two-types, a convex-type with reflectance 1.0 in w = λ1 ∼ λ2 and 0.0 otherwise, or a concave-type with reflectance 0.0 in w = λ1 ∼ λ2 and 1.0 otherwise. It takes a high computation cost to search the optimal color candidates in high precision and to create the 3D color gamut. In addition, the human visual spectral responses to the optimal color spectra remain unknown. This paper (1) proposes an alternative simple method for creating the optimal color gamut with GBD (Gamujt Boundary Descriptor) technique, and (2) clarifies how human vision spectrally respond to the optimal colors based on Matrix-R theory, for the first time which was unknown until now, and (3) presents centroid-invariant novel color gamut expansion method considering the optimal color as an ideal target and finally apply it to actual low-saturation images to verify its effect.