A fuzzy-neural system for removal of the color cast for digitally captured images under unknown illuminants

This paper proposes a novel color balance technique by establishing a fuzzy inference system. A database is constructed to include certain properties of various color samples captured under standard illuminants. Next, a fuzzy system is established, whose configuration and parameters are determined using the aforementioned database. Finally, test image captured under unknown illuminant may be passed through the fuzzy system to produce a set of ratios for correcting and removing the color cast. An experiment and comparative study justify that the suggested approach is preferable to existing methods with regard to execution time and the performance.

[1]  B. Wandell,et al.  Natural scene-illuminant estimation using the sensor correlation , 2002, Proc. IEEE.

[2]  Ingeborg Tastl,et al.  Gamut Constrained Illuminant Estimation , 2006, International Journal of Computer Vision.

[3]  Cheng-Lun Chen,et al.  Formulating and solving a class of optimization problems for high-performance gray world automatic white balance , 2011, Appl. Soft Comput..

[4]  David A. Forsyth,et al.  A novel algorithm for color constancy , 1990, International Journal of Computer Vision.

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

[6]  Deane B. Judd Sensibility to Color-Temperature Change as a Function of Temperature* , 1933 .

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

[8]  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.

[9]  Graham D. Finlayson,et al.  Improving gamut mapping color constancy , 2000, IEEE Trans. Image Process..

[10]  Sung-Jea Ko,et al.  A video camera system with enhanced zoom tracking and auto white balance , 2002, IEEE Trans. Consumer Electron..

[11]  Chiou-Shann Fuh,et al.  Automatic White Balance with Color Temperature Estimation , 2007, 2007 Digest of Technical Papers International Conference on Consumer Electronics.

[12]  B. Wandell,et al.  Standard surface-reflectance model and illuminant estimation , 1989 .

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

[14]  Cheng-Lun Chen,et al.  Intelligent color temperature estimation using fuzzy neural network with application to automatic white balance , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[15]  Brian V. Funt,et al.  A comparison of computational color constancy Algorithms. II. Experiments with image data , 2002, IEEE Trans. Image Process..