Light mixture estimation for spatially varying white balance

SIGGRAPH'08: International Conference on Computer Graphics and Interactive Techniques, ACM SIGGRAPH 2008 Papers 2008

Volumn , Issue , 2008, Pages

  Hsu, Eugene ^a   Mertens, Tom ^b   Paris, Sylvain ^c   Avidan, Shai ^c   Durand, Fredo ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b HASSELT UNIVERSITY   (Belgium)

^c ADOBE RESEARCH   (United States)

Author keywords

Color constancy; Computational photography; Image processing; White balance

Indexed keywords

CAMERAS; COLOR; COLOR IMAGE PROCESSING; COMPUTER GRAPHICS; DIGITAL IMAGE STORAGE; IMAGE PROCESSING; IMAGING SYSTEMS; INTERACTIVE COMPUTER GRAPHICS; LIGHTING; MIXTURES; PHOTOGRAPHY; PIPELINES;

COLOR CASTS; COLOR CONSTANCY; COMPUTATIONAL PHOTOGRAPHY; INDOOR/OUTDOOR; LIGHT COLORS; MIXTURE ESTIMATIONS; POST EXPOSURES; RELIGHTING; SINGLE IMAGES; UNDER-CONSTRAINED; WHITE BALANCE;

COLOR PHOTOGRAPHY;

EID: 57649098488     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

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 14,1 (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. HONG, H., GORTLER, S., AND ZLCKLER, 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., IKEUCH1, 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 WEUER, 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.