A Fuzzy Entropy-Constrained Vector Quantizer Design Algorithm and Its Applications to Image Coding

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概要

• 論文の詳細を見る

• In this paper, a novel variable-rate vector quantizer (VQ) design algorithm using fuzzy clustering technique is presented. The algorithm, termed fuzzy entropy-constrained VQ (FECVQ) design algorithm, has a better rate-distortion performance than that of the usual entropy-constrained VQ (ECVQ) algorithm for variable-rate VQ design. When performing the fuzzy clustering, the FECVQ algorithm considers both the usual squared-distance measure, and the length of channel index associated with each codeword so that the average rate of the VQ can be controlled. In addition, the membership function for achieving the optimal clustering for the design of FECVQ are derived. Simulation results demonstrate that the FECVQ can be an effective alternative for the design of variable-rate VQs.

• 社団法人電子情報通信学会の論文
• 1999-06-25

著者

• Hong S‐l

  Department Of Electrical Engineering Chung Yuan Christian University

• Hwang Wen-jyi

  Department Of Electrical Engineering Chung Yuan Christian University

• HONG Sheng-Lin

  Department of Electrical Engineering, Chung Yuan Christian University

関連論文

• A Novel Variable-Rate Classified Vector Quantizer Design Algorithm for Image Coding
• A Fuzzy Entropy-Constrained Vector Quantizer Design Algorithm and Its Applications to Image Coding
• A Novel Competitive Learning Technique for the Design of Variable-Rate Vector Quantizers with Reproduction Vector Training in the Wavelet Domain

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