Color images enhancement in spatial domain

In digital image processing applications, image enhancement algorithms are often used to bring out details that is vague and emphasize certain features in an image. The aim of this thesis is to enhance the contrast of low contrast color images without causing any artificial effect on images. In this study, image enhancement is considered as an optimization problem. Due to the effective performance in reel world optimization problems metaheuristic algorithms are preferred in this study. Also because the reel world problems generally have multiple objectives multi objective optimization algorithms are utilized. In this study, contrasts of low contrast color images are enhanced by utilizing single and multi objective genetic algorithm, particle swarm optimization algorithm and artificial bee colony algorithm. In this study, eight standard color test images are used. After the algorithms used in this study are applied to the test images the obtained results are evaluated based on the quality metrics; peak signal to noise ratio, structural similarity index metric, contrast improvement index and color enhancement factor. Thus the effect of both single and multi objective optimization techniques on image enhancement is observed. As a result of both visual and objective evaluations of obtained results, it is observed that contrasts of images have improved by applying single and multi objective image enhancement algorithms that used in this study without causing any artificial appearance.