Vector Quantization Using the Hybrid Swarm Intelligence Algorithms

Vector Quantization (VQ) was the powerful technique in image compression. Generating a good codebook is an important part of VQ. There are various algorithms in order to generate an optimal codebook. Recently, Swarm Intelligence (SI) algorithms were adapted to obtain the near-global optimal codebook of VQ. In this paper, we proposed a new method based on a hybrid particle swarm optimization (PSO) and firefly algorithm (FA) to construct the codebook of VQ. The proposed method used PSO algorithm as the initial of FA to develop the VQ. This method is called PSO-FA model. Experimental results indicate that the proposed model is faster than FA. Furthermore, the reconstructed images get higher quality than FA, but it is no significant superiority to the PSO algorithm.