A NOVEL APPROACH OF VECTOR QUANTIZATION USING MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR GENERATING EFFICIENT CODEBOOK

The objective of this proposed work is to develop an efficient compression algorithm without compromising image quality. Mostly vector quantization designs a local optimal codebook for compressing images effectively. In recent days, several optimization algorithms are used to generate global codebook. Particle swarm optimization algorithm is one of the efficient evolutionary computing algorithms which helps to reduce the computation time and generates an efficient codebook as well. This paper presents a novel approach of Modified Particle Swarm Optimization(MPSO) technique using vector quantization technique. The initial swarm is formed out of image blocks with high variance. Furthermore the random values for updating the gbest and pbest in velocity update equation has been replaced with optimal values which has significantly improved the image quality. Experimental results on test images show that MPSO suits well for all types of images, yielding very high PSNR values compared to Standard PSO and K-means algorithms.