Codebook Optimization in Vector Quantization Using Genetic Algorithm

This paper presents genetic algorithm (GA) as a part of evolutionary computing for vector quantizer design in color image compression. Vector quantization, a lossy method to compress the image data in spatial domain. So the quality of the decompressed image is degraded. In order to achieve trade off between quality of compression along with good compression ratio, the vector quantizer must be designed optimally. Hence we have applied genetic algorithm on the optimal design of the codebook generation in VQ, where codebook could minimize the average distortion between a given training set and the codebook. The performance of decompression is observed by using image quality measure as PSNR for the images with RGB color space. Comparison of genetic algorithm (GA) based codebook method and random codebook method is done.