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1-bit compressed sensing based on reweighting approximate message passing
Author(s): Jingjing Si; Yinbo Cheng; Pei Xu
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Paper Abstract

1-bit compressed sensing (1-bit CS) examines the efficient acquisition of sparse signals via linear measurement systems followed by a 1-bit quantizer. In this paper, we discuss 1-bit CS reconstruction in the scenario that the sparsity level of the signal is unknown. We introduce reweighting approximate message passing (AMP) into the 1-bit CS problem and propose the binary iterative reweighting AMP algorithm (AMP-BRW). This algorithm performs binary reweighting AMP in the iterative process, which conforms to the binary manner of the 1-bit CS measurements and inherits the advantages of AMP. Simulation results show that AMP-BRW can realize 1-bit CS reconstruction without the prior knowledge of the sparse level of the signal. Moreover, AMP-BRW can achieve higher reconstruction performance and higher convergence performance than the original binary iterative reweighted algorithm.

Paper Details

Date Published: 14 August 2019
PDF: 7 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111793Y (14 August 2019); doi: 10.1117/12.2539752
Show Author Affiliations
Jingjing Si, Yanshan Univ. (China)
Yinbo Cheng, Ocean College of Hebei Agricultural Univ. (China)
Pei Xu, Yanshan Univ. (China)
Ocean College of Hebei Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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