Color Image Enhancement Using Particle Swarm Optimization (PSO)

Image enhancement is aimed to improve image quality by maximizing the information content in the input image. In this article a PSO based hue preserving color image enhancement technique is proposed. The process is as follows. Image enhancement is considered as an optimization problem and particle swarm optimization (PSO) is used to solve it. The quality of the intensity image is improved by a parameterized transformation function, in which parameters are optimized by PSO based on an objective function. The intensity transformation function uses local and global information of the input image and the objective function considers the entropy and edge information to measure the image quality. The enhanced color image is then obtained by scaling, which sometimes leads to gamut problem for few pixels. Rescaling is done to the saturation component to remove the gamut problem. The algorithm is tested on several color images and results are compared with two other popular color image enhancement techniques like hue-preserving color image enhancement without gamut problem (HPCIE) and a genetic algorithm based approach to color image enhancement (GACIE). Visual analysis, detail and background variance of the resultant images are reported. It has been found that the proposed method produces better results compared to other two methods.