Paper
14 August 2019 1-bit compressed sensing based on reweighting approximate message passing
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Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111793Y (2019) https://doi.org/10.1117/12.2539752
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China
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.
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Jingjing Si, Yinbo Cheng, and Pei Xu "1-bit compressed sensing based on reweighting approximate message passing", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111793Y (14 August 2019); https://doi.org/10.1117/12.2539752
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KEYWORDS
Reconstruction algorithms

Binary data

Compressed sensing

Signal processing

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