Light Mixture Estimation for Spatially Varying White Balance
Eugene Hsu, Tom Mertens, Sylvain Paris, Shai Avidan, Frédo Durand
In ACM Transactions on Graphics, 27(3), August 2008.
Abstract: White balance is a crucial step in the photographic pipeline. It ensures the proper rendition of images by eliminating color casts due to differing illuminants. Digital cameras and editing programs provide white balance tools that assume a single type of light per image, such as daylight. However, many photos are taken under mixed lighting. We propose a white balance technique for scenes with two light types that are specified by the user. This covers many typical situations involving indoor/outdoor or flash/ambient light mixtures. Since we work from a single image, the problem is highly underconstrained. Our method recovers a set of dominant material colors which allows us to estimate the local intensity mixture of the two light types. Using this mixture, we can neutralize the light colors and render visually pleasing images. Our method can also be used to achieve post-exposure relighting effects.
Keyword(s): color constancy, computational photography, image processing, white balance
@article{Hsu:2008:LME,
author = {Eugene Hsu and Tom Mertens and Sylvain Paris and Shai Avidan and Frédo Durand},
title = {Light Mixture Estimation for Spatially Varying White Balance},
journal = {ACM Transactions on Graphics},
volume = {27},
number = {3},
pages = {70:1--70:7},
month = aug,
year = {2008},
}
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