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The search functionality is under construction.

A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.

- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.7 pp.2035-2040

- Publication Date
- 2008/07/01

- Publicized

- Online ISSN
- 1745-1361

- DOI
- 10.1093/ietisy/e91-d.7.2035

- Type of Manuscript
- PAPER

- Category
- Image Processing and Video Processing

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ShanXue CHEN, FangWei LI, WeiLe ZHU, TianQi ZHANG, "Fast Searching Algorithm for Vector Quantization Based on Subvector Technique" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 7, pp. 2035-2040, July 2008, doi: 10.1093/ietisy/e91-d.7.2035.

Abstract: A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.

URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.7.2035/_p

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@ARTICLE{e91-d_7_2035,

author={ShanXue CHEN, FangWei LI, WeiLe ZHU, TianQi ZHANG, },

journal={IEICE TRANSACTIONS on Information},

title={Fast Searching Algorithm for Vector Quantization Based on Subvector Technique},

year={2008},

volume={E91-D},

number={7},

pages={2035-2040},

abstract={A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.},

keywords={},

doi={10.1093/ietisy/e91-d.7.2035},

ISSN={1745-1361},

month={July},}

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TY - JOUR

TI - Fast Searching Algorithm for Vector Quantization Based on Subvector Technique

T2 - IEICE TRANSACTIONS on Information

SP - 2035

EP - 2040

AU - ShanXue CHEN

AU - FangWei LI

AU - WeiLe ZHU

AU - TianQi ZHANG

PY - 2008

DO - 10.1093/ietisy/e91-d.7.2035

JO - IEICE TRANSACTIONS on Information

SN - 1745-1361

VL - E91-D

IS - 7

JA - IEICE TRANSACTIONS on Information

Y1 - July 2008

AB - A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.

ER -