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Proceedings Paper

Statistic model for coding subband images using VQ and arithmetic coding
Author(s): Andre Nicoulin; Marco Mattavelli
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Paper Abstract

A new entropy coding algorithm for the compression of subband images is presented. By combining vector quantization (VQ) and scalar quantization (SQ) with entropy coding, the proposed scheme exploits the remaining statistical dependencies among the subband samples, and keeps an optimal control on local distortion by scalar quantization. The system is based on a statistical model which uses VQ information to generate low entropy probability tables for an arithmetic coder. The bit rate can be shared between VQ-rate and SQ-rate, allowing many possible configurations in terms of performances and implementation complexity. The proposed system shows improved performances when compared with other existing methods.

Paper Details

Date Published: 1 November 1992
PDF: 11 pages
Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); doi: 10.1117/12.131484
Show Author Affiliations
Andre Nicoulin, Swiss Federal Institute of Technology (Switzerland)
Marco Mattavelli, Swiss Federal Institute of Technology (Switzerland)


Published in SPIE Proceedings Vol. 1818:
Visual Communications and Image Processing '92
Petros Maragos, Editor(s)

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