Robust mixed one-bit compressive sensing

被引：4

作者：

Huang, Xiaolin ^{[1
,2
]}

Yang, Haiyan ^{[1
,2
]}

Huang, Yixing ^{[3
]}

Shi, Lei ^{[4
]}

He, Fan ^{[1
,2
]}

Maier, Andreas ^{[3
]}

Yan, Ming ^{[5
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Inst Med Robot, Shanghai, Peoples R China

[2] Shanghai Jiao Tong Univ, Key Lab Syst Control & Informat Proc, MOE, Shanghai, Peoples R China

[3] Friedrich Alexander Univ Erlangen Nurnberg, Pattern Recognit Lab, Erlangen, Germany

[4] Fudan Univ, Sch Math Sci, Shanghai Key Lab Contemporary Appl Math, Shanghai, Peoples R China

[5] Michigan State Univ, Dept Math, Dept Computat Math Sci & Engn, E Lansing, MI 48824 USA

来源：

SIGNAL PROCESSING | 2019年 / 162卷

基金：

中国国家自然科学基金;

关键词：

Compressive sensing; One-bit; Signal recovery; Image reconstruction; RECONSTRUCTION; ALGORITHM; NOISE;

D O I：

10.1016/j.sigpro.2019.04.011

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

When a measurement falls outside the quantization or measurable range, it becomes saturated and cannot be used in conventional signal recovery methods. Aiming at acquiring information from noisy saturated and regular measurements, we in this paper propose a new signal recovery method called mixed one-bit compressive sensing (M1 bit-CS) and develop an efficient algorithm in the framework of alternating direction methods of multipliers. Numerical experiments on one-dimensional symmetric signals and two-dimensional image reconstruction from computed tomography verify the effectiveness of M1 bit-CS on signal recovery from saturated measurements. (C) 2019 Elsevier B.V. All rights reserved.

引用

页码：161 / 168

页数：8

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