Abstract:

This paper is based on the DCT(Discrete Cosine Transform) basic principle and characteristics, andits purpose is to break the shackles of the unified characteristics of traditional DCT transform matrix, for theoptimization on the DCT transformation matrix of image information, to achieve the image compression efficiently.Firstly, compare the reconstructed image by DCT with the original image. Then, use genetic algorithm to find theoptimal solution by minimizing the mean square error, in order to optimize the DCT transform matrix coefficient.Finally, use the transform kernel optimized for image processing. Experiment was carried out from blocking theimage and setting genetic initial parameters, and the experimental results indicate that for the linear edge andtexture feature images of small block processing, when the number of population is 40 ~ 60, the length of thestring is 8, the crossover probability is 0. 7 ~ 0. 8, and the mutation probability is 0. 007 ~ 0. 008,the DCToptimization method based on genetic algorithm for image compression to reach the best effects.

Key words: discrete cosine transform ( DCT) optimization, genetic algorithm, image compression, mean
square error