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Optical Engineering

Subband image coding using jointly localized filter banks and entropy coding based on vector quantization
Author(s): Andre Nicoulin; Marco Mattavelli; Wei Li; Murat Kunt
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Paper Abstract

A method for image compression based on subband decomposition is presented. We describe a new filter bank design method for image coding applications and a new entropy coding algorithm for the compression of subband images. A set of relevant optimization criteria is defined for the filter bank design. For the compression, a composite source model is defined by combining vector quantization (VQ) and scalar quantization (SQ) with entropy coding. In the proposed scheme, VQ exploits the remaining statistical dependencies among the subband samples, while SQ allows an optimal control on local distortions. The system is based on a statistical model that uses VQ information to generate low entropy probability tables for an arithmetic coder. The bit rate can be shared between the VQ rate and the SQ rate, allowing many possible configurations in terms of performance and implementation complexity. The proposed system shows improved performance when compared with other existing methods.

Paper Details

Date Published: 1 July 1993
PDF: 13 pages
Opt. Eng. 32(7) doi: 10.1117/12.139808
Published in: Optical Engineering Volume 32, Issue 7
Show Author Affiliations
Andre Nicoulin, Ecole Polytechnique Federale de Lausanne (Switzerland)
Marco Mattavelli, Ecole Polytechnique Federale de Lausanne (Switzerland)
Wei Li, Swiss Federal Institute of Technology (Switzerland)
Murat Kunt, Swiss Federal Institute of Technology (Switzerland)

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