The role of bright pixels in illumination estimation

Final Program and Proceedings - IS and T/SID Color Imaging Conference

Volumn , Issue , 2012, Pages 41-46

  Vaezi Joze, Hamid Reza ^a   Drew, Mark S ^a   Finlayson, Graham D ^b   Troncoso Rey, Perla Aurora ^b  

^a SIMON FRASER UNIVERSITY   (Canada)

^b UNIVERSITY OF EAST ANGLIA   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COLOUR CONSTANCY; ILLUMINATION ESTIMATION; INPUT IMAGE; PIXEL VALUES; SIMPLE METHOD;

ALGORITHMS; APPLICATION PROGRAMS; COLOR; ESTIMATION; LIGHT SOURCES;

PIXELS;

EID: 84876741578     PISSN: 10831304     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (33)

1. K. Barnard. Improvements to gamut mapping colour constancy algorithms. In European conference on computer vision, pages 390-403, 2000.
2. K. Barnard, L. Martin, B. Funt, and A. Coath. A data set for colour research. Color Research and Applications, 27:147-151, 2002.
3. G. Buchsbaum. A spatial processor model for object colour perception. J. Franklin Inst., 310:1-26, 1980. (Pubitemid 11434416)
4. A. Choudhury and G. Medioni. Perceptually motivated automatic color contrast enhancement. In CRICV09: Color and Reflectance in Imaging and Computer Vision Workshop, pages 1893-1900, 2009.
5. F. Ciurea and B. V. Funt. A large image database for color constancy research. In IS&T/SID Color Imaging Conference, pages 160-164, 2003.
6. Mark S. Drew, Hamid Reza Vaezi Joze, and Graham D. Finlayson. Specularity, the zeta-image, and information-theoretic illuminant estimation. In CPCV2012: European Conference on Computer Vision Workshop on Color and Photometry in Computer Vision, Oct. 2012.
7. G. Finlayson and S. Hordley. Improving gamut mapping color constancy. IEEE Transactions on Image Processing, 9(10):1774-1783, 2000.
8. G. D. Finlayson and G. Schaefer. Convex and non-convex illumination constraints for dichromatic color constancy. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 598-605, 2001.
9. G. D. Finlayson and G. Schaefer. Solving for colour constancy using a constrained dichromatic reflection model. Int. J. Comput. Vision, 42(3):127-144, 2001. (Pubitemid 32680800)
10. G.D. Finlayson. Color in perspective. IEEE Trans. Patt. Anal. and Mach. Intell., 18:1034-1038, 1996. (Pubitemid 126773913)
11. G.D. Finlayson and E. Trezzi. Shades of gray and colour constancy. In Twelfth Color Imageing Conference: Color, Science, Systems and Applications., pages 37-41, 2004.
12. D.A. Forsyth. A novel approach to color constancy. In Int. Conf. on Computer Vision '88, pages 9-18, 1988.
13. B. Funt. Hdr dataset, 2010. http://www.cs.sfu.ca/colour/data/funt-hdr.
14. B. Funt and L. Shi, The effect of exposure on maxrgb color constancy. In SPIE Volume 7527 Human Vision and Electronic Imaging XV, 2010.
15. B. Funt and L. Shi. The rehabilitation of maxrgb. In 18th Color Imaging Conference, pages 256-259, 2010.
16. Peter Gehler, Carsten Rother, Andrew Blake, Tom Minka, and Toby Sharp. Bayesian color constancy revisited. In CVPR '08: Computer Vision and Pattern Recognition, 2008.
17. A. Gijsenij and T. Gevers. Color constancy using natural image statistics and scene semantics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(4):687-698, 2011.
18. A. Gijsenij, T. Gevers, and J. van de Weijer. Computational color constancy: Survey and experiments. IEEE Transactions on Image Processing, 20:2475-2489, 2011.
19. Arjan Gijsenij, Theo Gevers, and Joost Weijer. Generalized gamut mapping using image derivative structures for color constancy. International Journal of Computer Vision, 86(2-3):127-139, October 2008.
20. G. Healey. Using color for geometry-insensitive segmentation. Journal of Optics Soceity of America A, 6(6):920-937, 1989.
21. S. D. Hordley. Scene illuminant estimation: past, present, and future. Color Research and Application, 31(4):303-314, 2006.
22. H.R. Veazi Joze and M.S. Drew. White patch gamut mapping colour constancy. In Int. Conf. on Image Proc. IEEE, 2012.
23. G.J. Klinker, S.A. Shafer, and T. Kanade. The measurement of high-lights in color images. Int. J. Comput. Vision, 2:7-32, 1988.
24. E. Land. The retinex theory of color vision. Scientific American, 237(6):108-128, December 1977.
25. H. Lee. E. Breneman. and C. Schulte. Modeling light reflection for computer color vision. IEEE Trans. Pattern Analysis and Machine Intelligence, 12(4):402-409, 1990. (Pubitemid 20689483)
26. H.-C. Lee. Method for computing the scene-illuminant chromaticity from specular highlights. J. Opt. Soc. Am. A, 3:1694-1699, 1986.
27. T M. Lehmann and C. Palm. Color line search for illuminant estimation in real-world scenes. The Journal of the Optical Society of America A, 18(11):2679-2691, 2001.
28. S.A. Shafer. Using color to separate reflection components. Color Res. Appl., 10:210-218, 1985.
29. Lilong Shi and Brian Funt. Re-processed version of the gehler color constancy dataset of 568 images, 2010. http://www.cs.sfu.ca/colour/data.
30. Robby T. Tan and Katsushi Ikeuchi. Separating reflection components of textured surfaces using a single image. IEEE Trans. Patt. Anal. and Mach. Intell., 27:870-877, 2005.
31. J. van de Weijer and T. Gevers. Color constancy based on the grey-edge hypothesis. In Int. Conf. on Image Proc., pages II:722-725, 2005.
32. Joost van de Weijer, Cordelia Schmid, and Jakob Verbeek. Using high-level visual information for color constancy. In IEEE Conference on Computer Vision (ICCV), 2007.
33. G. Wyszecki and W.S. Stiles. Color Science: Concepts and Methods, Quantitative Data and Formulas. Wiley, New York, 2nd edition, 1982.