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Sorted random matrix for Orthogonal Matching Pursuit

conference contribution
posted on 2019-02-21, 00:00 authored by Zhenglin WangZhenglin Wang, I Lee
Orthogonal Matching Pursuit (OMP) algorithm is widely applied to compressive sensing (CS) image signal recovery because of its low computation complexity and its ease of implementation. However, OMP usually needs more measurements than some other recovery algorithms in order to achieve equal-quality reconstructions. This article firstly illustrates the fundamental idea of OMP and the specific algorithm steps. And then, two limitations leading to the previous issue are addressed. Finally, a sorted random matrix is proposed to be used as a measurement matrix to improve those two limitations. The experimental results show the proposed measurement matrix is able to help OMP make a great progress on the quality of recovered approximations. © 2010 IEEE.

History

Parent Title

2010 International Conference on Digital Image Computing: Techniques and Applications

Start Page

116

End Page

120

Number of Pages

5

Start Date

2010-12-01

Finish Date

2010-12-03

ISBN-13

9781424488162

Location

Sydney, Australia

Publisher

IEEE

Place of Publication

Piscataway, NJ

Peer Reviewed

  • Yes

Open Access

  • No

External Author Affiliations

University of South Australia

Era Eligible

  • Yes

Name of Conference

Digital Image Computing: Techniques and Applications (DICTA 2010)

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