The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cet article, un nouvel algorithme de conception de quantificateur vectoriel (VQ) à débit variable utilisant la technique de regroupement flou est présenté. L'algorithme, appelé algorithme de conception VQ à contrainte d'entropie floue (FECVQ), présente de meilleures performances de distorsion de débit que celles de l'algorithme VQ à contrainte d'entropie (ECVQ) habituel pour la conception de VQ à débit variable. Lors de l'exécution du regroupement flou, l'algorithme FECVQ prend en compte à la fois la mesure habituelle de la distance carrée et la longueur de l'indice de canal associé à chaque mot de code afin que le débit moyen du VQ puisse être contrôlé. De plus, les fonctions d'appartenance permettant d'obtenir le clustering optimal pour la conception de FECVQ sont dérivées. Les résultats de simulation démontrent que le FECVQ peut être une alternative efficace pour la conception de VQ à taux variable.
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Wen-Jyi HWANG, Sheng-Lin HONG, "A Fuzzy Entropy-Constrained Vector Quantizer Design Algorithm and Its Applications to Image Coding" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 6, pp. 1109-1116, June 1999, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_6_1109/_p
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@ARTICLE{e82-a_6_1109,
author={Wen-Jyi HWANG, Sheng-Lin HONG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Fuzzy Entropy-Constrained Vector Quantizer Design Algorithm and Its Applications to Image Coding},
year={1999},
volume={E82-A},
number={6},
pages={1109-1116},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - A Fuzzy Entropy-Constrained Vector Quantizer Design Algorithm and Its Applications to Image Coding
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1109
EP - 1116
AU - Wen-Jyi HWANG
AU - Sheng-Lin HONG
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1999
AB - 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.
ER -