Vector Quantization Using a Modified Firefly Algorithm for Image Compression

Vector Quantization (VQ) is 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 modified firefly algorithm (MFA) to construct the codebook of VQ. The proposed method merged genetic crossover operator with FA to develop the VQ. This method is called MFA model. Experimental results indicate that the reconstructed images generated by the proposed model is get higher quality than FA and it’s about one percent, but it is no significant superiority to the PSO algorithm. Furthermore, MFA is slower than FA.