Using Optimal Surface Reflectance Functions to Study Color Space Properties

Abstract

We present a computational definition of the Optimal Color Stimuli surface, which corresponds to the limit of physically realizable surface spectral reflectance functions. We can use this surface to quantify and visualize color space properties, as we demonstrate for the CIE XYZ and L*a*b* spaces, as well as our own neurophysiologically-based NPP space. We then extend the technique to compute a representative set of surface spectral reflectance functions, all contained within the volume bounded by the OCS surface, and their corresponding representations in a color space. This set of spectra can be used to generate training sets for a backpropagation algorithm computing color space transforms, for example. 1 The research reported in this paper was done while the author was a member of the SNePS Research Group at the department of Computer Science, State University of New York at Buffalo, and was supported in part by Equipment Grant No. EDUD-US-932022 from SUN Microsystems Computer Corp..