Generic red, green, and blue images can be regarded as data sources of coarse (three bins) local spectra, typical data volumes are 104 to 107 spectra. Image data bases often yield hundreds or thousands of images, yielding data sources of 109 to 1010 spectra. There is usually no calibration, and there often are various nonlinear image transformations involved. However, we argue that sheer numbers make up for such ambiguity. We propose a model of spectral data mining that applies to the sublunar realm, spectra due to the scattering of daylight by objects from the generic terrestrial environment. The model involves colorimetry and ecological physics. Whereas the colorimetry is readily dealt with, one needs to handle the ecological physics with heuristic methods. The results suggest evolutionary causes of the human visual system. We also suggest effective methods to generate red, green, and blue color gamuts for various terrains.
Keywords: ecological optics; natural colors; opponent channels; spectral correlation.