DPCM design by genetic algorithm

Digitized images have been used widely in nowadays-industrial applications; however, digital images cost a huge storage capacity so as to lead the transmission bandwidth constrained. Therefore, image compression technique was developed to solve this drawback. Differential Pulse Code Modulation (DPCM) is the most widely used method among the entire predictive image coding schemes. It is based on the notation of quantizing a prediction error signal after the prediction operation to reduce the original data complexity. The design of the predictor influences the performance of the whole DPCM. Therefore, the predictor constitutes a central topic in DPCM system. In this paper, we make efforts for the design of predictor by genetic algorithm (GA). By the operations of crossover and mutation, several predictor coefficients are yielded after hundred of generations. The predictor generated by the GA outperforms the current eight different predictive schemes in Joint Photographic Experts Group lossless (JPEG-LS) still image compression standard. Because JPEG-LS compression scheme is the widest used lossless compression methods currently, the results yielded contribute to the applications of compression.