Combining White-Patch Retinex and the Gray World Assumption to Achieve Color Constancy for Multiple Illuminants

The human visual system is able to correctly determine the color of objects irrespective of the actual light they reflect. This ability to compute color constant descriptors is an important problem for computer vision research. We have developed a parallel algorithm for color constancy. The algorithm is based on two fundamental theories of color constancy, the gray world assumption and the white-patch retinex algorithm. The algorithm's performance is demonstrated on several images where objects are illuminated by multiple illuminants.

[1]  L. Maloney,et al.  Color constancy: a method for recovering surface spectral reflectance. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[2]  Marc Ebner A parallel algorithm for color constancy , 2004, J. Parallel Distributed Comput..

[3]  David H. Foster,et al.  Space-average scene colour used to extract illuminant information , 1997 .

[4]  D H Brainard,et al.  Analysis of the retinex theory of color vision. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[5]  Marc Ebner,et al.  Evolving Color Constancy for an Artificial Retina , 2001, EuroGP.

[6]  Brian V. Funt,et al.  Learning Color Constancy , 1996, CIC.

[7]  Brian V. Funt,et al.  Color Constancy for Scenes with Varying Illumination , 1997, Comput. Vis. Image Underst..

[8]  Graham D. Finlayson,et al.  Color by Correlation , 1997, CIC.

[9]  Graham D. Finlayson,et al.  Color in Perspective , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  M D'Zmura,et al.  Mechanisms of color constancy. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[11]  Berthold K. P. Horn Robot vision , 1986, MIT electrical engineering and computer science series.

[12]  Brian V. Funt,et al.  Is Machine Colour Constancy Good Enough? , 1998, ECCV.

[13]  Bernt Schiele,et al.  Comprehensive Colour Image Normalization , 1998, ECCV.

[14]  Leif H. Finkel,et al.  A multistage neural network for color constancy and color induction , 1995, IEEE Trans. Neural Networks.

[15]  Mark S. Drew,et al.  Color constancy computation in near-Mondrian scenes using a finite dimensional linear model , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[16]  John K. Tsotsos,et al.  From [R, G, B] to Surface Reflectance: Computing Color Constant Descriptors in Images , 1987, IJCAI.

[17]  B. Regan John Dalton’s Colour Vision Legacy , 1998 .

[18]  David A. Forsyth,et al.  A Novel Approach To Colour Constancy , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[19]  M. H. Brill,et al.  Contributions to the theory of invariance of color under the condition of varying illumination , 1981 .

[20]  Rodney M. Goodman,et al.  A real-time neural system for color constancy , 1991, IEEE Trans. Neural Networks.

[21]  Brian V. Funt,et al.  Committee-Based Color Constancy , 1999, CIC.

[22]  G. Buchsbaum A spatial processor model for object colour perception , 1980 .