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Journal of Electronic Imaging

Illumination estimation via nonnegative matrix factorization
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Paper Abstract

The problem of illumination estimation for color constancy and automatic white balancing of digital color imagery can be viewed as the separation of the image into illumination and reflectance components. We propose using nonnegative matrix factorization with sparseness constraints to separate these components. Since illumination and reflectance are combined multiplicatively, the first step is to move to the logarithm domain so that the components are additive. The image data is then organized as a matrix to be factored into nonnegative components. Sparseness constraints imposed on the resulting factors help distinguish illumination from reflectance. The proposed approach provides a pixel-wise estimate of the illumination chromaticity throughout the entire image. This approach and its variations can also be used to provide an estimate of the overall scene illumination chromaticity.

Paper Details

Date Published: 12 September 2012
PDF: 13 pages
J. Electron. Imaging. 21(3) 033022 doi: 10.1117/1.JEI.21.3.033022
Published in: Journal of Electronic Imaging Volume 21, Issue 3
Show Author Affiliations
Lilong Shi, Samsung Semiconductor, Inc. (United States)
Brian V. Funt, Simon Fraser Univ. (Canada)
Weihua Xiong, OmniVision Technologies, Inc. (United States)

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