Fuzzy-VQ image compression based hybrid PSOGSA optimization algorithm

The transmission speed of big data in multimedia, social networking, and web services, can be enhanced by image compression technology. Fuzzy vector quantization (VQ) image compression is a significant tool for achieving a codebook to illuminate lineaments of big data. A functionality combination of PSO and GSA algorithms, with parallel running, have been used to design a fuzzy-VQ image compression system. The improvement of the compressed image quality has been executed by carrying out suitable parameters selection using the proposed algorithm. Comparative study between sophisticated learning schemes and Linde-Buzo-Gray (LBG) based VQ learning process has been introduced. The proposed algorithms provide an achievement in the behavior of pure image compression.