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Sorted random matrix for Orthogonal Matching Pursuit
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.
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Parent Title
2010 International Conference on Digital Image Computing: Techniques and ApplicationsStart Page
116End Page
120Number of Pages
5Start Date
2010-12-01Finish Date
2010-12-03ISBN-13
9781424488162Location
Sydney, AustraliaPublisher
IEEEPlace of Publication
Piscataway, NJPublisher DOI
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Peer Reviewed
- Yes
Open Access
- No
External Author Affiliations
University of South AustraliaEra Eligible
- Yes
Name of Conference
Digital Image Computing: Techniques and Applications (DICTA 2010)Usage metrics
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