A SVD-Based 2DOMP Algorithm for Compressed Image Sensing

被引：0

作者：

Zhang, Cheng ^{[1
]}

Chen, Qianwen ^{[1
]}

Wang, Meiqin ^{[1
]}

Wang, Dong ^{[1
]}

Wei, Sui ^{[1
]}

机构：

[1] Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei, Anhui, Peoples R China

来源：

PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON COMMUNICATION AND INFORMATION PROCESSING (ICCIP 2018) | 2018年

关键词：

compressed sensing; separable compressed sensing; compressed imaging; two-dimensional orthogonal matching pursuit; singular value decomposition; SIGNAL RECOVERY;

D O I：

10.1145/3290420.3290457

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We use the singular value decomposition of the separable measurement matrices to obtain the optimized separable reconstruction matrices and optimize the measurements. A two-dimensional orthogonal matching pursuit optimization algorithm based on singular value decomposition is proposed. Numerical experiments demonstrate that our proposed 2DOMP-SVD algorithm can significantly improve reconstruction quality and signal to noise ratio. Moreover, separable imaging operator arise naturally in many optical implementations and can satisfy the requirements for both the measurement matrix and the reconstruction matrix individually. And this design is suitable for general separable linear system.

引用

页码：77 / 80

页数：4

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