An improved fast codeword search algorithm based on Hadamard transform

Abstract

A fast neighbor codeword search algorithm for vector quantization based on Hadamard transform is presented in this paper. Before the encoding process, the Hadamard transform is calculated on all the codewords in the codebook, and then sorted in the ascending order of their first elements. During the encoding process, firstly the Hadamard transform is applied to the input vector, and its characteristic values are calculated. Secondly, the initial match codeword is selected from the codeword whose Hadamard transform first element is nearest to the input vector. Finally, the best-match codeword to the input vector is found by using the four elimination criteria. Experimental results show that the proposed algorithm has reduced greatly codeword search time and computational complexity. Besides, it is much more efficient than the current existing nearest neighbor codeword search algorithm on the performance. Therefore, it is an efficient nearest neighbor codeword search algorithm.