IEICE TRANSACTIONS on Information
Image Coding Based on Classified Side-Match Vector Quantization
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E83-D No.12 pp.2189-2192
- Publication Date
- 2000/12/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Image Processing, Image Pattern Recognition
Authors
Keyword
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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},}
Copy
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 -
English
