Improved Codebook Design Algorithm Based on Principal Component Analysis

This paper proposes an improved codebook design algorithm for image compression, which solves the problem that the codebook design algorithm based on principal component analysis and genetic algorithm obtains the worse codebooks than those computed by LBG algorithm when the codebook size is larger than 64. By the algorithm, we first reduce the dimensionality of the training vectors using principal component analysis, and then use the near global optimal searching ability of genetic algorithm to compute the codebook. Experimental results show that our algorithm outperforms the primary algorithm and the popular LBG algorithm in terms of image compression performance, and the computing time needed by our algorithm is also shorter than the LBG algorithm.