The artificial bee colony algorithm for vector quantization in image compression

Abstract

The vector quantization was a powerful technique in image compression. The widely used method such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. Recently, particle swarm optimization was adapted to obtain the near-global optimal codebook of vector quantization. The alterative method called the quantum particle swarm optimization was developed to improve the results of original PSO algorithm. The honey bee mating optimization was used to develop the algorithm for vector quantization. In this paper, we proposed a new method based on the artificial bee colony (ABC) algorithm to construct the codebook of vector quantization. The proposed method uses LBG method as the initial of ABC algorithm to develop the VQ algorithm. This method is called ABC-LBG algorithm. The ABC-LBG algorithm is compared with four algorithms described above. Experimental results showed that the ABC-LBG algorithm is more reliable and the reconstructed images get higher quality compared to other methods.