Sparse approximation using fast matching pursuit

被引：0

作者：

Gan, Tao ^{[1
]}

He, Yanmin ^{[1
]}

Zhu, Weile ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu 610054, Peoples R China

来源：

2007 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATION SYSTEMS, VOLS 1 AND 2 | 2007年

关键词：

sparse approximation; matching pursuit; anisotropic refinement;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Matching pursuit based on geometric dictionary has shown to be a powerful tool for sparse image representation. ne main obstacle to its application in real world is the computational complexity. In this paper, a modified algorithm is presented to address this issue. The dictionary with anisotropic refinement atoms is used to provide the approximation ability. Meanwhile the pursuit implementation is significantly speeded up by employing both sequential and parallel techniques. Experimental results show that compared to the latest matching pursuit approach, the proposed algorithm offers a speedup of 27.7-36.7 while maintaining the approximation quality. It is very promising for flexible image coding at low bit rate.

引用

页码：407 / 410

页数：4

共 50 条

[1] Fast Sparse Signal Approximation Via Matching Pursuit
Wang, M. J.
Yu, W. D.
Wang, Y.
[J]. 2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC), 2013, : 1944 - 1947
[2] Sparse Approximation by Matching Pursuit Using Shift-Invariant Dictionary
Skretting, Karl
Engan, Kjersti
[J]. IMAGE ANALYSIS, SCIA 2017, PT I, 2017, 10269 : 362 - 373
[3] SPARSE APPROXIMATION WITH AN ORTHOGONAL COMPLEMENTARY MATCHING PURSUIT ALGORITHM
Rath, Gagan
Guillemont, Christine
[J]. 2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, 2009, : 3325 - 3328
[4] Average Performance of Orthogonal Matching Pursuit (OMP) for Sparse Approximation
Schnass, Karin
[J]. IEEE SIGNAL PROCESSING LETTERS, 2018, 25 (12) : 1865 - 1869
[5] Stabilized Stepwise Orthogonal Matching Pursuit for Sparse Signal Approximation
Wang, Mingjiang
Liu, Guanghong
Zhang, De
Han, Kuoye
Chen, Yanmin
[J]. 2017 INTERNATIONAL CONFERENCE ON CLOUD TECHNOLOGY AND COMMUNICATION ENGINEERING (CTCE2017), 2017, 910
[6] Sparse classification using Group Matching Pursuit
Zheng, Shuai
Ding, Chris
[J]. NEUROCOMPUTING, 2019, 338 : 83 - 91
[7] SPARSE DICTIONARY LEARNING FOR SEISMIC NOISE ATTENUATION USING A FAST ORTHOGONAL MATCHING PURSUIT ALGORITHM
Zhou, Yatong
Li, Shuhua
Xie, Jianyong
Zhang, Dong
Chen, Yangkang
[J]. JOURNAL OF SEISMIC EXPLORATION, 2017, 26 (05): : 433 - 454
[8] Sparse Representation Classification via Fast Matching Pursuit for Face Recognition
Abdel-Sayed, Michael M.
Khattab, Ahmed
Abu-Elyazeed, Mohamed F.
[J]. 2017 PROCEEDINGS OF THE JAPAN-AFRICA CONFERENCE ON ELECTRONICS, COMMUNICATIONS, AND COMPUTERS (JAC-ECC), 2017, : 103 - 106
[9] A Fast Algorithm for Sparse Channel Estimation via Orthogonal Matching Pursuit
Jiang, Xue
Zeng, Wen-Jun
Cheng, En
[J]. 2011 IEEE 73RD VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2011,
[10] A Fast Multiple Orthogonal Matching Pursuit Algorithm for Jointly Sparse Recovery
Xiang Long
Xiang Hu
Li Shaodong
Ma Xiaoyan
[J]. 2016 CIE INTERNATIONAL CONFERENCE ON RADAR (RADAR), 2016,

← 1 2 3 4 5 →