A fast encoding algorithm for vector quantization using dynamic subvector technique

The encoding of vector quantization (VQ) needs expensive computation for searching the closet codeword to the input vectors. In order to reduce computation burden, Pan et al. have developed an efficient full-search-equivalent algorithm by using the characteristics of the sums and variances of a vector and its two fixed subvectors recently. However, some computational redundancies still exist in it. In this paper, we introduce a technique to efficiently partition a vector into two dynamic subvectors according to the patterns inside the block (or vector) and then further improve the computation load given by Pan's method. Experimental results show that the proposed method is superior to other algorithms in terms of processing time and the number of distortion calculations. Compared to Pan's algorithm, our algorithm can further reduce the processing time and the number of distortion calculations for various codebook sizes by 14.7% to 41.3% and 14.9% to 44.6%, respectively.