Color Constancy Beyond Bags of Pixels

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Color Constancy Beyond Bags of Pixels

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Title: Color Constancy Beyond Bags of Pixels
Author: Hirakawa, Keigo; Chakrabarti, Ayan; Zickler, Todd

Note: Order does not necessarily reflect citation order of authors.

Citation: Chakrabarti, Ayan, Keigo Hirakawa, and Todd Zickler. 2008. Color constancy beyond bags of pixels. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska, June 23-28, 2008, ed. IEE CVPR 2008, 1-6. Los Alamitos, California: IEEE.
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Abstract: Estimating the color of a scene illuminant often plays a central role in computational color constancy. While this problem has received significant attention, the methods that exist do not maximally leverage spatial dependencies between pixels. Indeed, most methods treat the observed color (or its spatial derivative) at each pixel independently of its neighbors. We propose an alternative approach to illuminant estimation-one that employs an explicit statistical model to capture the spatial dependencies between pixels induced by the surfaces they observe. The parameters of this model are estimated from a training set of natural images captured under canonical illumination, and for a new image, an appropriate transform is found such that the corrected image best fits our model.
Published Version: http://dx.doi.org/10.1109/CVPR.2008.4587664
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:2886301

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  • FAS Scholarly Articles [6463]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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