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
이 기사에서는 이미지 압축을 위해 적응형 블록 분류를 사용하는 사이드 매치 유한 상태 벡터 양자화라고 하는 효율적인 벡터 양자화(VQ) 방식을 제시합니다. 영상을 구성하는 블록의 평균값 외에 영상에 포함된 에지 정보를 활용합니다. 좋은 품질의 이미지를 유지하면서 낮은 비트율 코딩을 달성하기 위해 주변 블록을 활용하여 현재 블록의 클래스를 예측합니다. 본 코딩 방식에서 이미지 블록은 주로 에지 블록(edge block)과 비에지 블록(non-edge block)으로 분류됩니다. 코딩 효율성을 높이기 위해 에지 블록과 비에지 블록을 각각 다른 클래스로 추가로 재분류합니다. 또한, 입력 블록의 클래스를 예측하고 해당 클래스에 작은 상태 코드북을 적용함으로써 영상 인코딩을 위한 비트 수를 크게 줄일 수 있다. 제안된 코딩 방식의 개선은 다른 VQ 기술과 비교하여 매력적입니다.
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부
Shinfeng D. LIN, Shih-Chieh SHIE, "Side-Match Finite-State Vector Quantization with Adaptive Block Classification for Image Compression" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 8, pp. 1671-1678, August 2000, doi: .
Abstract: In this article, an efficient vector quantization (VQ) scheme called side-match finite-state vector quantization with adaptive block classification is presented for image compression. It makes use of edge information contained in image in additional to the average values of blocks forming the image. In order to achieve low bit rate coding while preserving good quality images, neighboring blocks are utilized to predict the class of current block. Image blocks are mainly classified as edge blocks and non-edge blocks in this coding scheme. To improve the coding efficiency, edge blocks and non-edge blocks are further reclassified into different classes, respectively. Moreover, the number of bits for encoding an image is greatly reduced by foretelling the class of input block and applying small state codebook in corresponding class. The improvement of the proposed coding scheme is attractive as compared with other VQ techniques.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_8_1671/_p
부
@ARTICLE{e83-d_8_1671,
author={Shinfeng D. LIN, Shih-Chieh SHIE, },
journal={IEICE TRANSACTIONS on Information},
title={Side-Match Finite-State Vector Quantization with Adaptive Block Classification for Image Compression},
year={2000},
volume={E83-D},
number={8},
pages={1671-1678},
abstract={In this article, an efficient vector quantization (VQ) scheme called side-match finite-state vector quantization with adaptive block classification is presented for image compression. It makes use of edge information contained in image in additional to the average values of blocks forming the image. In order to achieve low bit rate coding while preserving good quality images, neighboring blocks are utilized to predict the class of current block. Image blocks are mainly classified as edge blocks and non-edge blocks in this coding scheme. To improve the coding efficiency, edge blocks and non-edge blocks are further reclassified into different classes, respectively. Moreover, the number of bits for encoding an image is greatly reduced by foretelling the class of input block and applying small state codebook in corresponding class. The improvement of the proposed coding scheme is attractive as compared with other VQ techniques.},
keywords={},
doi={},
ISSN={},
month={August},}
부
TY - JOUR
TI - Side-Match Finite-State Vector Quantization with Adaptive Block Classification for Image Compression
T2 - IEICE TRANSACTIONS on Information
SP - 1671
EP - 1678
AU - Shinfeng D. LIN
AU - Shih-Chieh SHIE
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2000
AB - In this article, an efficient vector quantization (VQ) scheme called side-match finite-state vector quantization with adaptive block classification is presented for image compression. It makes use of edge information contained in image in additional to the average values of blocks forming the image. In order to achieve low bit rate coding while preserving good quality images, neighboring blocks are utilized to predict the class of current block. Image blocks are mainly classified as edge blocks and non-edge blocks in this coding scheme. To improve the coding efficiency, edge blocks and non-edge blocks are further reclassified into different classes, respectively. Moreover, the number of bits for encoding an image is greatly reduced by foretelling the class of input block and applying small state codebook in corresponding class. The improvement of the proposed coding scheme is attractive as compared with other VQ techniques.
ER -