Multispectral processing without spectra

It is often the case that multiplications of whole spectra, component by component, must be carried out,for example when light reflects from or is transmitted through materials. This leads to particularly taxing calculations, especially in spectrally based ray tracing or radiosity in graphics, making a full-spectrum method prohibitively expensive. Nevertheless, using full spectra is attractive because of the many important phenomena that can be modeled only by using all the physics at hand. We apply to the task of spectral multiplication a method previously used in modeling RGB-based light propagation. We show that we can often multiply spectra without carrying out spectral multiplication. In previous work [J. Opt. Soc. Am. A 11, 1553 (1994)] we developed a method called spectral sharpening, which took camera RGBs to a special sharp basis that was designed to render illuminant change simple to model. Specifically, in the new basis, one can effectively model illuminant change by using a diagonal matrix rather than the 3 x 3 linear transform that results from a three-component finite-dimensional model [G. Healey and D. Slater, J. Opt. Soc. Am. A 11, 3003 (1994)]. We apply this idea of sharpening to the set of principal components vectors derived from a representative set of spectra that might reasonably be encountered in a given application. With respect to the sharp spectral basis, we show that spectral multiplications can be modeled as the multiplication of the basis coefficients. These new product coefficients applied to the sharp basis serve to accurately reconstruct the spectral product. Although the method is quite general, we show how to use spectral modeling by taking advantage of metameric surfaces, ones that match under one light but not another, for tasks such as volume rendering. The use of metamers allows a user to pick out or merge different volume structures in real time simply by changing the lighting.