Estimating Illumination Chromaticity via Support Vector Regression

Xiong, W. and Funt, B., Estimating Illumination Chromaticity via Support Vector Regression, Journal of Imaging Science and Technology Vol. 50, No.4 pp. 341-348, July/August 2006.

Abstract:

Support vector regression is applied to the problem of estimating the chromaticity of the light illuminating a scene from a color histogram of an image of the scene. Illumination estimation is fundamental to white balancing digital color images and to under- standing human color constancy. Under controlled experimental conditions, the support vector method is shown to perform well. Its performance is compared to other published methods including neu- ral network color constancy, color by correlation, and shades of gray.

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