Genetic image enhancement based on saturation feedback

In this paper an adaptive approach for color image enhancement is proposed. In this approach, the saturation feedback technique is used as a means of supplementing color image shmpness and contrast. This technique of the saturation feedback can serve to bring out image details that have low luminance contrast. In the technique, the feedback parameters are the key component and are usually determined manually. In order to realize the adaptive color image enhancement, the genetic algorithm is employed to search global optimal parameters for saturation feedback automatically. The detailed procedures are described in the paper. Experimental results on color images show the feasibility of the proposed method.

[1]  Lotfi A. Zadeh,et al.  Fuzzy Algorithms , 1968, Inf. Control..

[2]  Martin D. Levine,et al.  A Genetic Algorithm for Primitive Extraction , 1991, International Conference on Genetic Algorithms.

[3]  Hong Yan,et al.  Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition , 1996, Advances in Fuzzy Systems - Applications and Theory.

[4]  Christopher J. Taylor,et al.  Model-based image interpretation using genetic algorithms , 1992, Image Vis. Comput..

[5]  Bir Bhanu,et al.  Adaptive image segmentation using a genetic algorithm , 1989, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Robin N. Strickland,et al.  Digital Color Image Enhancement Based On The Saturation Component , 1987 .

[7]  Haim Levkowitz,et al.  GLHS: A Generalized Lightness, Hue, and Saturation Color Model , 1993, CVGIP Graph. Model. Image Process..

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  Hong Yan,et al.  Improved method for color image enhancement based on luminance and color contrast , 1994, J. Electronic Imaging.