Compressed maximum descent algorithm for codebook generation

Chrissavgi Dre; Stavroula Giannopoulou; Costas E. Goutis

doi:10.1117/12.185942

16 September 1994 Compressed maximum descent algorithm for codebook generation

Chrissavgi Dre, Stavroula Giannopoulou, Costas E. Goutis

Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/10.1117/12.185942
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States

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.

Citation Download Citation

Chrissavgi Dre, Stavroula Giannopoulou, and Costas E. Goutis "Compressed maximum descent algorithm for codebook generation", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); https://doi.org/10.1117/12.185942

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