IEICE TRANSACTIONS on Information
Optimal Permutation Based Block Compressed Sensing for Image Compression Applications
Summary :
Block compressed sensing (CS) with optimal permutation is a promising method to improve sampling efficiency in CS-based image compression. However, the existing optimal permutation scheme brings a large amount of extra data to encode the permutation information because it needs to know the permutation information to accomplish signal reconstruction. When the extra data is taken into consideration, the improvement in sampling efficiency of this method is limited. In order to solve this problem, a new optimal permutation strategy for block CS (BCS) is proposed. Based on the proposed permutation strategy, an improved optimal permutation based BCS method called BCS-NOP (BCS with new optimal permutation) is proposed in this paper. Simulation results show that the proposed approach reduces the amount of extra data to encode the permutation information significantly and thereby improves the sampling efficiency compared with the existing optimal permutation based BCS approach.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.1 pp.215-224
- Publication Date
- 2018/01/01
- Publicized
- 2017/10/20
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017EDP7087
- Type of Manuscript
- PAPER
- Category
- Image Processing and Video Processing
Authors
Yuqiang CAO
Chongqing University
Weiguo GONG
Chongqing University
Bo ZHANG
Chongqing Communication Institute
Fanxin ZENG
Chongqing Communication Institute
Sen BAI
Chongqing Communication Institute
Keyword
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Yuqiang CAO, Weiguo GONG, Bo ZHANG, Fanxin ZENG, Sen BAI, "Optimal Permutation Based Block Compressed Sensing for Image Compression Applications" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 1, pp. 215-224, January 2018, doi: 10.1587/transinf.2017EDP7087.
Abstract: Block compressed sensing (CS) with optimal permutation is a promising method to improve sampling efficiency in CS-based image compression. However, the existing optimal permutation scheme brings a large amount of extra data to encode the permutation information because it needs to know the permutation information to accomplish signal reconstruction. When the extra data is taken into consideration, the improvement in sampling efficiency of this method is limited. In order to solve this problem, a new optimal permutation strategy for block CS (BCS) is proposed. Based on the proposed permutation strategy, an improved optimal permutation based BCS method called BCS-NOP (BCS with new optimal permutation) is proposed in this paper. Simulation results show that the proposed approach reduces the amount of extra data to encode the permutation information significantly and thereby improves the sampling efficiency compared with the existing optimal permutation based BCS approach.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017EDP7087/_p
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@ARTICLE{e101-d_1_215,
author={Yuqiang CAO, Weiguo GONG, Bo ZHANG, Fanxin ZENG, Sen BAI, },
journal={IEICE TRANSACTIONS on Information},
title={Optimal Permutation Based Block Compressed Sensing for Image Compression Applications},
year={2018},
volume={E101-D},
number={1},
pages={215-224},
abstract={Block compressed sensing (CS) with optimal permutation is a promising method to improve sampling efficiency in CS-based image compression. However, the existing optimal permutation scheme brings a large amount of extra data to encode the permutation information because it needs to know the permutation information to accomplish signal reconstruction. When the extra data is taken into consideration, the improvement in sampling efficiency of this method is limited. In order to solve this problem, a new optimal permutation strategy for block CS (BCS) is proposed. Based on the proposed permutation strategy, an improved optimal permutation based BCS method called BCS-NOP (BCS with new optimal permutation) is proposed in this paper. Simulation results show that the proposed approach reduces the amount of extra data to encode the permutation information significantly and thereby improves the sampling efficiency compared with the existing optimal permutation based BCS approach.},
keywords={},
doi={10.1587/transinf.2017EDP7087},
ISSN={1745-1361},
month={January},}
Copy
TY - JOUR
TI - Optimal Permutation Based Block Compressed Sensing for Image Compression Applications
T2 - IEICE TRANSACTIONS on Information
SP - 215
EP - 224
AU - Yuqiang CAO
AU - Weiguo GONG
AU - Bo ZHANG
AU - Fanxin ZENG
AU - Sen BAI
PY - 2018
DO - 10.1587/transinf.2017EDP7087
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2018
AB - Block compressed sensing (CS) with optimal permutation is a promising method to improve sampling efficiency in CS-based image compression. However, the existing optimal permutation scheme brings a large amount of extra data to encode the permutation information because it needs to know the permutation information to accomplish signal reconstruction. When the extra data is taken into consideration, the improvement in sampling efficiency of this method is limited. In order to solve this problem, a new optimal permutation strategy for block CS (BCS) is proposed. Based on the proposed permutation strategy, an improved optimal permutation based BCS method called BCS-NOP (BCS with new optimal permutation) is proposed in this paper. Simulation results show that the proposed approach reduces the amount of extra data to encode the permutation information significantly and thereby improves the sampling efficiency compared with the existing optimal permutation based BCS approach.
ER -
English
