Storage- and entropy-constrained classified vector quantization

Wen Jyi Hwang*, Yue Shen Tu, Yeong Cherng Lu


研究成果: 雜誌貢獻期刊論文同行評審

3 引文 斯高帕斯(Scopus)


This paper presents a novel variable-rate classified vector quantizer (CVQ) design algorithm for the applications of image coding. The design algorithm, termed storage- and entropy-constrained classified vector quantization (SECCVQ) algorithm, is able to control the rate and the storage size of the CVQ. The algorithm allocates the rate and storage size available to each class of the VQ optimally so that the average distortion of the SECCVQ is minimized. The classification of image blocks is based on the edge orientation of each block in the wavelet domain. To reduce the arithmetic complexity of the CVQ, we employ a novel partial distance codeword search algorithm in the wavelet domain. Simulation results show that the SECCVQ enjoys low average distortion, low encoding complexity, high visual perception quality, and is well-suited for very low bit rate image coding.

頁(從 - 到)1252-1261
期刊IEEE Transactions on Consumer Electronics
出版狀態已發佈 - 1997

ASJC Scopus subject areas

  • 媒體技術
  • 電氣與電子工程


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