VQ-Based Fuzzy Compression Systems Designs through Bacterial Foraging Particle Swarm Optimization Algorithm

The bacterial-foraging-based swarm intelligent algorithm called bacterial foraging particle swarm optimization (BFPSO) is proposed to design the vector quantization (VQ)-based fuzzy image compression systems. It can improve the compressed image quality in processing the large amount of image-patterns. BFPSO combines the inspired behaviors of bacterial foraging mode and the PSO learning scheme to simultaneously obtain the benefits of fast convergence and self-adapt learning ability. The evolutionary BFPSO algorithm is achieve to automatically design appropriate parameters of fuzzy VQ-based systems by the proper codebooks selection. The developed BFPSO learning scheme compared with LBG based VQ learning method are presented to demonstrate its great result in the real image.