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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dalam makalah ini, algoritma reka bentuk kuantiti vektor kadar pembolehubah (VQ) novel menggunakan teknik pengelompokan kabur dibentangkan. Algoritma, yang disebut algoritma reka bentuk VQ (FECVQ) terkandas entropi kabur, mempunyai prestasi herotan kadar yang lebih baik daripada algoritma VQ (ECVQ) terkekang entropi biasa untuk reka bentuk VQ kadar berubah. Apabila melakukan pengelompokan kabur, algoritma FECVQ mempertimbangkan kedua-dua ukuran jarak kuasa dua biasa dan panjang indeks saluran yang dikaitkan dengan setiap kata kod supaya kadar purata VQ boleh dikawal. Di samping itu, fungsi keahlian untuk mencapai pengelompokan optimum untuk reka bentuk FECVQ diperolehi. Keputusan simulasi menunjukkan bahawa FECVQ boleh menjadi alternatif yang berkesan untuk reka bentuk VQ kadar berubah-ubah.
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Salinan
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
Salinan
@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},}
Salinan
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 -