Fast VQ Encoding Using Subvector Technique

In order to speed up the VQ encoding process, it is beneficial to firstly estimate how large the Euclidean distance is between the input vector and a candidate codeword by using appropriate low dimensional features of a vector instead of an immediate Euclidean distance computation. The sum, the partial sums and the partial variances of a vector are used together as the appropriate features in this paper. Utilizing these features between the input vector and a candidate codeword, we obtain some inequalities of eliminating unnecessary codewords. First the inequality based on the sum is used for terminating the searching process. Then, using other inequalities based on subvector sum and variance, more unnecessary codewords are eliminated. During the search process for code, the proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the reduction of computation is outstanding in the computational complexity and the number of distortion calculations against full search method.