Fast search algorithm for vector quantization using means and variances of code words

Chang-Hsing Lee; Ling-Hwei Chen

doi:10.1117/12.206770

21 April 1995 Fast search algorithm for vector quantization using means and variances of code words

Chang-Hsing Lee, Ling-Hwei Chen

Proceedings Volume 2501, Visual Communications and Image Processing '95; (1995) https://doi.org/10.1117/12.206770
Event: Visual Communications and Image Processing '95, 1995, Taipei, Taiwan

Abstract

Vector Quantization has been applied to low-bit-rate speech and image compression. One of the most serious problems for vector quantization is the high computational complexity of searching for the closest codeword in the codebook design and encoding processes. To overcome this problem, a fast algorithm, under the assumption that the distortion is measured by the squared Euclidean distance, will be proposed to search for the closest codeword to an input vector. Using the means and variances of codewords, the algorithm can reject many codewords that are impossible to be candidates for the closest codeword to the input vector and hence save a great deal of computation time. Experimental results confirm the effectiveness of the proposed method.

Citation Download Citation

Chang-Hsing Lee and Ling-Hwei Chen "Fast search algorithm for vector quantization using means and variances of code words", Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); https://doi.org/10.1117/12.206770

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