An image compression using self-organization with genetic algorithm

Abstract

In this report, as a method of image compression, we have developed a new method of self-organized image compression. In the method, many nodes are yielded and self-organized according to a gray scale level of image data. Additionally, we have used a genetic algorithm to remove some useless nodes among created clusters so that a high performance optimum structure is realized by as small a number nodes as possible. In addition, we use orthogonal wavelet analysis in the proposed method. In the wavelet domain, we execute self-organization clustering and also check out the performance of the method.