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Recovering the spectral distribution of the illumination from spectral data by highlight analysis

The problem of color constancy for discounting illumination color to obtain the apparent color of the object has been the topic of much research in computer vision. By assuming the neutral interface reflection and dichromatic reflection with highlights (i.e. highlights have the same color as the illuminant) various methods have been proposed aiming at recovering the illuminant color from color highlight analysis. In general, these methods are based on three color stimuli to approximate color. In this contribution, we estimate the spectral distribution from surface reflection using spectral information obtained by a spectrograph. The imaging spectrograph provides a spectral range at each pixel covering the visible wavelength range. Our method differ from existing methods by using a robust clustering technique to obtain the body and surface components in a multi-spectral space. These components determine the direction of the illumination spectral color. Then, we recover the illumination spectral power distribution by using principal component analysis for all wavelengths. To obtain the most reliable estimate of the spectral power distribution of the illuminant, all possible combinations of wavelengths are used to generate the optimal averaged estimation of the spectral power distribution of the scene illuminant. Our method is restricted to images containing a substantial amount of body reflection and highlights.