Integrated Particle Swarm Optimization and Genetic Algorithm Based Compression for Reduction of Blocking Artifacts

Abstract: Image compression has become very important tool in digital image processing. The main objective of the compression is to reduce the amount or unwanted data while retaining the information in the image. The goal behind is to save the amount of memory required to save the image(s) or to utilize network bandwidth in efficient manner. Transform-based compression is extensively used for image compression. But transform based methods introduce blocking artifacts in the output image. The compression may also results in ringing artifacts around edges. The ringing artifacts are in general more difficult to characterize and remove than the block transform compression artifacts. This paper has proposed a new compression technique which has integrated the Particle swarm optimization (PSO) and Genetic algorithm (GA) based compression in wavelet domain for reduction of blocking artifacts in images. The comparison also drawn among the proposed and the existing technique based upon the various standard quality metrics of the compression techniques. No techniques is acceptable in every case