Light mixture estimation for spatially varying white balance

Authors:
Eugene Hsu;Tom Mertens;Sylvain Paris;Shai Avidan;Frédo Durand
Affiliations:
Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory;Hasselt University, Belgium;Adobe Systems, Inc.;Adobe Systems, Inc.;Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory
Venue:
ACM SIGGRAPH 2008 papers
Year:
2008

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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.