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Proceedings Paper

Compressed maximum descent algorithm for codebook generation
Author(s): Chrissavgi Dre; Stavroula Giannopoulou; Costas E. Goutis
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Paper Abstract

A vital step in building a vector quantizer is to generate an optimal codebook. Among the algorithms presented in the literature, the Maximum Descent (MD) algorithm appears to be a promising alternative codevector generation technique to the generalized Lloyd (LBG) algorithm, when dealing with vector quantization of images. In this paper, a novel vector quantization codebook generation approach is presented. The algorithm uses an MD codebook as an initial codebook and a compression of this codebook is then achieved based on a simple feature clustering technique. According to this technique, we attempt to arrange the codevectors of the MD codebook in a way that prefixed number of clusters results. The centroids of the resulted clusters form a reduced MD codebook. Using this new technique we can produce codebooks with about 0.2 - 0.6 db improvement in peak-signal to noise ratio and a reduction of 10% - 20% in the codebook size compared to the LBG algorithm.

Paper Details

Date Published: 16 September 1994
PDF: 8 pages
Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185942
Show Author Affiliations
Chrissavgi Dre, Univ. of Patras (Greece)
Stavroula Giannopoulou, Univ. of Patras (Greece)
Costas E. Goutis, Univ. of Patras (Greece)

Published in SPIE Proceedings Vol. 2308:
Visual Communications and Image Processing '94
Aggelos K. Katsaggelos, Editor(s)

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