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Proceedings Paper

Fast search algorithm for vector quantization using means and variances of code words
Author(s): Chang-Hsing Lee; Ling-Hwei Chen
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Paper 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.

Paper Details

Date Published: 21 April 1995
PDF: 10 pages
Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206770
Show Author Affiliations
Chang-Hsing Lee, National Chiao Tung Univ. (Taiwan)
Ling-Hwei Chen, National Chiao Tung Univ. (Taiwan)


Published in SPIE Proceedings Vol. 2501:
Visual Communications and Image Processing '95
Lance T. Wu, Editor(s)

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