Abstract
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.
Highlights
We consider the colors of essentially the sublunary sphere of Aristotelian physics
We propose a model of spectral data mining that applies to the sublunar realm, involving spectra that are mainly due to the scattering of daylight by objects from the generic terrestrial environment
The structure of the Kubelka–Munk result is that the nonlinear part of the theory is packaged in the left side of Equation (4), whereas the right side of this equation describes fundamental physical causes—responsible for the spectral articulation—which are dominated by linear processes
Summary
We consider the colors of essentially the sublunary sphere of Aristotelian physics (itself derived from Greek astronomy). We consider a highly simplified model of the sublunar realm in which the radiant spectra are spectrally selectively attenuated versions of the daylight spectrum This implements ‘‘object colors.’’ For simplicity, we use a standard daylight spectrum available for download on the Internet (www.cie.co.at/index.php/LEFTMENUE/DOWNLOADS; see Figure 3). The structure of the Kubelka–Munk result is that the nonlinear part of the theory is packaged in the left side of Equation (4), whereas the right side of this equation describes fundamental physical causes—responsible for the spectral articulation—which are dominated by linear processes We use these observations as a heuristic. The colors of the distant ground plane and the low sky become very similar at the horizon (Middleton, 1952) Such facts of ecological physics are quite robust in the sense that they survive noncalibration and likely maltreatment of image processing.
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