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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
O quantizador vetorial de correspondência lateral classificado, CSMVQ, já foi apresentado para codificação de imagens com baixa taxa de bits. Ele explora um classificador de bloco para decidir a qual classe o vetor de entrada pertence usando as variações das palavras-código superior e esquerda. No entanto, este classificador de bloco não leva em consideração a variação do próprio vetor de entrada atual. Esta carta apresenta um novo CSMVQ no qual um classificador de blocos de dois níveis é usado para classificar vetores de entrada e dois livros de códigos mestres diferentes são usados para gerar o livro de códigos de estado de acordo com a variância do vetor de entrada. Resultados experimentais comprovam a eficácia do CSMVQ proposto.
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Zhe-Ming LU, Jeng-Shyang PAN, Sheng-He SUN, "Image Coding Based on Classified Side-Match Vector Quantization" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 12, pp. 2189-2192, December 2000, doi: .
Abstract: The classified side-match vector quantizer, CSMVQ, has already been presented for low-bit-rate image encoding. It exploits a block classifier to decide which class the input vector belongs to using the variances of the upper and left codewords. However, this block classifier doesn't take the variance of the current input vector itself into account. This letter presents a new CSMVQ in which a two-level block classifier is used to classify input vectors and two different master codebooks are used for generating the state codebook according to the variance of the input vector. Experimental results prove the effectiveness of the proposed CSMVQ.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_12_2189/_p
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@ARTICLE{e83-d_12_2189,
author={Zhe-Ming LU, Jeng-Shyang PAN, Sheng-He SUN, },
journal={IEICE TRANSACTIONS on Information},
title={Image Coding Based on Classified Side-Match Vector Quantization},
year={2000},
volume={E83-D},
number={12},
pages={2189-2192},
abstract={The classified side-match vector quantizer, CSMVQ, has already been presented for low-bit-rate image encoding. It exploits a block classifier to decide which class the input vector belongs to using the variances of the upper and left codewords. However, this block classifier doesn't take the variance of the current input vector itself into account. This letter presents a new CSMVQ in which a two-level block classifier is used to classify input vectors and two different master codebooks are used for generating the state codebook according to the variance of the input vector. Experimental results prove the effectiveness of the proposed CSMVQ.},
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - Image Coding Based on Classified Side-Match Vector Quantization
T2 - IEICE TRANSACTIONS on Information
SP - 2189
EP - 2192
AU - Zhe-Ming LU
AU - Jeng-Shyang PAN
AU - Sheng-He SUN
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2000
AB - The classified side-match vector quantizer, CSMVQ, has already been presented for low-bit-rate image encoding. It exploits a block classifier to decide which class the input vector belongs to using the variances of the upper and left codewords. However, this block classifier doesn't take the variance of the current input vector itself into account. This letter presents a new CSMVQ in which a two-level block classifier is used to classify input vectors and two different master codebooks are used for generating the state codebook according to the variance of the input vector. Experimental results prove the effectiveness of the proposed CSMVQ.
ER -