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Proceedings Paper

Joint optimization of lattice vector quantizer and entropy coder in subband coding
Author(s): Won-Ha Kim; Yu-Hen Hu; Truong Q. Nguyen
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Paper Abstract

This paper presents an algorithm that jointly optimizes a lattice vector quantizer (LVQ) and an entropy coder in a subband coding at all ranges of bit rate. Estimation formulas for both entropy and distortion of lattice quantized subband images are derived. From these estimates, we then develop dynamic algorithm optimizing the LVQ and entropy coder together for a given entropy rate. Compared to previously reported min-max approaches, or approaches using asymptotic distortion bounds, the approach reported in this paper quickly designs a highly accurate optimal entropy- constrained LVQ at all range of bit rates. The corresponding wavelet-based image coder has better coding performance comparing with other subband coders that use entropy- constrained LVQ, especially at low bit rates.

Paper Details

Date Published: 3 April 1997
PDF: 12 pages
Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); doi: 10.1117/12.271766
Show Author Affiliations
Won-Ha Kim, Univ. of Wisconsin/Madison (United States)
Yu-Hen Hu, Univ. of Wisconsin/Madison (United States)
Truong Q. Nguyen, Univ. of Wisconsin/Madison (United States)


Published in SPIE Proceedings Vol. 3078:
Wavelet Applications IV
Harold H. Szu, Editor(s)

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