Adaptively Contrast Enhancement for Image with Genetic Algorithm
A new contrast enhancement algorithm for image is proposed with genetic algorithm (GA). In-complete Beta transform (IBT) is used to obtain non-linear gray transform curve. Transform parameters are determined by GA to obtain optimal gray transform parameters. In order to avoid the expensive time for traditional contrast enhancement algorithms, which search optimal gray transform parameters in the whole parameters space, a new criterion is proposed.Contrast type for original image is determined employing the new criterion. Parameters space is given respectively according to different contrast types, which shrinks parameters space greatly. The fitness function for GA is formed by two performance measures, namely, contrast measure and noise change measure. Then GA is used to determine the optimal set of IBT with the largest fitness function value. Experiment results show that the new algorithm is able to adaptively enhance the contrast of image.
Contrast enhancement In-complete Beta transform Genetic algorithm
Changjiang Zhang Xiaodong Wang Haoran Zhang
College of Mathematics, Physics and Information Engineering, Zhejiang Normal University Jinhua, Zhejiang Province 321004, China
国际会议
杭州
英文
402-404
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）