Genetic Adaptive Color Image Enhancement

Image enhancement is one of the important image processing techniques.It is used to improve image quality or extract the fine details in the degraded images.For color image enhancement,most existing enhancement techniques make use of the luminance,hue and saturation description of a color image.Because the saturation component often contains higher frequency spectral energy,i.e.image detail,than its luminance counterpart.A number of researchers present to feed back high-pass information from the saturation component as a means of supplementing color image sharpness and contrast.This technique of "saturation feedback" can serve to bring out image details that have low luminance contrast.Based on the technique,a lot of enhancement approaches have been proposed.But these approaches are parameter dependent.In other words,for each image,the author has to manually adjust feedback parameters so as to obtain satisfied enhancement images.Obviously,it is too troublesome to satisfy real time image processing. In this study,a genetic algorithm approach to color image enhancement is proposed,in which color image enhancement is formulated as an optimization problem.The genetic algorithm is an adaptive procedure that searches for good solutions by using a collection of search points known as a population in order to maximize some desirable criterion.Also,the genetic algorithm,as a stochastic random search technique,is known to use the accumulating information to prune the search space,while a purely random search ignores information about the environment.In the proposed approach,feedback parameters are optimized components.The fitness function for genetic algorithm is formed by fuzzy entropy and fuzzy contrast.Then genetic algorithm is used to determine the "optimal" feedback parameters with the largest fitness function value.This paper also discusses the detail procedures of encoding,selection,crossover and mutation in the genetic algorithm. Experiments are done on color aerial images.Based on the experimental results obtained in this study,the enhanced color images by the proposed approach are satisfied.This shows the feasibility of the proposed approach.