Evolutionary Image Enhancement Using Multi-Objective Genetic Algorithm
Dhirendra Pal Singh, Ashish Khare · International Journal of Image Graphics and Signal Processing · 2013
Image Processing is the art of examining, identifying and judging the significances of the Images. Image enhancement refers to attenuation, or sharpening, of image features such as edgels, boundaries, or contrast to make the processed image more useful for analysis. Image enhancement procedures utilize the computers to provide good and improved images for study by the human interpreters. In this paper we proposed a novel method that uses the Genetic Algorith m with Multi- objective criteria to find more enhance version of images. The proposed method has been verified with benchmark images in Image Enhancement. The simp le Genetic A lgorith m may not exp lore much enough to find out more enhanced image. In the proposed method three objectives are taken in to consideration. They are intensity, entropy and number of edgels. Proposed algorith m achieved automatic image enhancement criteria by incorporating the objectives (intensity, entropy, edges). We review some of the existing Image Enhancement technique. We also compared the results of our algorithms with another Genetic Algorithm based techniques. We expect that further imp rovements can be achieved by incorporating linear relationship between some other techniques.