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Optical Engineering

Jigsaw-puzzle vector quantization for image compression
Author(s): Chia-Hung Yeh
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Paper Abstract

A new finite-state vector quantization scheme called jigsaw-puzzle vector quantization (JPVQ) is proposed to provide better image quality, especially in the low bit rate context. For low bit rate image coding with conventional finite-state vector quantization (FSVQ) techniques, image quality degrades due to error propagation from one state to the next. The proposed JPVQ algorithm exploits the four-step side-match prediction technique to optimize the spatial continuity of each encoded block to improve the coding performance and reduce the error propagation effect. In the proposed coding scheme, an input block can be encoded by the jigsaw-puzzle block, the dynamic codebook, or the supercodebook. It is demonstrated with experimental results that JPVQ performs significantly better than traditional FSVQ techniques.

Paper Details

Date Published: 1 February 2004
PDF: 8 pages
Opt. Eng. 43(2) doi: 10.1117/1.1633777
Published in: Optical Engineering Volume 43, Issue 2
Show Author Affiliations
Chia-Hung Yeh, Univ. of Southern California (United States)

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