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Light mixture estimation for spatially varying white balance

Published: 01 August 2008 Publication History

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.

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References

[1]
Barnard, K., Finlayson, G. D., and Funt, B. V. 1997. Color constancy for scenes with varying illumination. Computer Vision and Image Understanding 65, 2 (Mar.), 311--321.
[2]
Brainard, D. H., and Freeman, W. T. 1997. Bayesian color constancy. Journal of the Optical Society of America 14, 7 (July), 1393--1411.
[3]
Buchsbaum, G. 1980. A spatial processor model for object colour perception. Journal of The Franklin Institute 310, 1 (July), 1--26.
[4]
Chong, H., Gortler, S., and Zickler, T. 2007. The von Kries hypothesis and a basis for color constancy. In IEEE International Conference on Computer Vision, 1--8.
[5]
Ebner, M. 2004. Color constancy using local color shifts. In European Conference on Computer Vision, 276--287.
[6]
Finlayson, G. D., and Hordley, S. D. 2000. Improving gamut mapping color constancy. IEEE Transactions on Image Processing 9, 10 (Oct.), 1774--1783.
[7]
Finlayson, G. D., Hordley, S. D., and Hubel, P. M. 2001. Color by correlation: A simple, unifying framework for color constancy. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 11 (Nov.), 1209--1221.
[8]
Finlayson, G. D. 1995. Color constancy in diagonal chromaticity space. In IEEE International Conference on Computer Vision, 218--223.
[9]
Forsyth, D. A. 1990. A novel algorithm for color constancy. International Journal of Computer Vision 5, 1 (Aug.), 5--36.
[10]
Gijsenij, A., and Gevers, T. 2007. Color constancy using natural image statistics. In IEEE Computer Vision and Pattern Recognition, 1--8.
[11]
Hough, P. V. C., 1962. Method and means of recognizing complex patterns. U.S. Patent 3,069,654.
[12]
Kawakami, R., Ikeuchi, K., and Tan, R. T. 2005. Consistent surface color for texturing large objects in outdoor scenes. In IEEE International Conference on Computer Vision, 1200--1207.
[13]
Kopf, J., Cohen, M. F., Lischinski, D., and Uyttendaele, M. 2007. Joint bilateral upsampling. ACM Transactions on Graphics 26, 3 (July), 96:1--96:5.
[14]
Land, E. H., and McCann, J. J. 1971. Lightness and Retinex theory. Journal of the Optical Society of America 61, 1 (Jan.), 1--11.
[15]
Levin, A., Lischinski, D., and Weiss, Y. 2004. Colorization using optimization. ACM Transactions on Graphics 23, 3 (Aug.), 689--694.
[16]
Levin, A., Lischinski, D., and Weiss, Y. 2006. A closed form solution to natural image matting. In IEEE Computer Vision and Pattern Recognition, 61--68.
[17]
Lischinski, D., Farbman, Z., Uyttendaele, M., and Szeliski, R. 2006. Interactive local adjustment of tonal values. ACM Transactions on Graphics 25, 3 (July), 646--653.
[18]
Omer, I., and Werman, M. 2004. Color lines: Image specific color representation. In Computer Vision and Pattern Recognition, 946--953.
[19]
Van de Weijer, J., and Gevers, T. 2005. Color constancy based on the grey-edge hypothesis. In IEEE International Conference on Image Processing, 722--725.
[20]
Wandell, B. A. 1995. Foundations of Vision. Sinauer Associates, Sunderland, MA.

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Published In

cover image ACM Transactions on Graphics
ACM Transactions on Graphics  Volume 27, Issue 3
August 2008
844 pages
ISSN:0730-0301
EISSN:1557-7368
DOI:10.1145/1360612
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2008
Published in TOG Volume 27, Issue 3

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Author Tags

  1. color constancy
  2. computational photography
  3. image processing
  4. white balance

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