A New Predictive Vector Quantization Method Using a Smaller Codebook

Abstract

For improving coding efficiency, a new predictive vector quantization (VQ) method was proposed in this paper. Two codebooks with different dimensionalities and different size were employed in our algorithm. The defined blocks are first classified based on variance. For smooth areas, the current processing vectors are sampled into even column vectors and odd column vectors. The even column vectors are encoded with the lower-dimensional and smaller size codebook. The odd ones are predicted using the decoded pixels from intra-blocks and inter-blocks at the decoder. For edge areas, the current processing vectors are encoded with traditional codebook to maintain the image quality. An efficient method for codebook design was also presented to improve the quality of the resulted codebook. The experimental comparisons with the other methods show good performance of our algorithm.

The work is supported by the Guang Dong Province Science Foundation for Program of Research Team (grant 04205783), the National Natural Science Foundation of China (Grant 60274006), the Natural Science Key Fund of Guang Dong Province, China (Grant 020826), the National Natural Science Foundation of China for Excellent Youth (Grant 60325310) and the Trans—Century Training Program.