A reformative algorithm for compressed sensing sparse signal recovery based on smoothed L0 norm

Yongtian Zhang, Xiaomei Chen*, Chao Zeng, Kun Gao, Haitong Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The SL0 algorithm for compressed sensing (CS) is an convex programming iterative reconstruction algorithm, which construct a smooth function to approximate the L0 norm and transform the NP-hard problem of minimization of the L0 norm into a convex optimization problem of the smooth function. Aiming at its shortcomings, this paper proposes a faster and more efficient reconstruction algorithm (CG-SL0), which uses the inverse trigonometric fraction function to approximate the L0 norm, and uses the conjugate gradient method to achieve optimization. Experimental results show that, the CG-SL0 algorithm has significant advantages in reconstruction quality and performance under the same test conditions.

Original languageEnglish
Title of host publicationNinth Symposium on Novel Photoelectronic Detection Technology and Applications
EditorsJunhao Chu, Wenqing Liu, Hongxing Xu
PublisherSPIE
ISBN (Electronic)9781510664432
DOIs
Publication statusPublished - 2023
Event9th Symposium on Novel Photoelectronic Detection Technology and Applications - Hefei, China
Duration: 21 Apr 202323 Apr 2023

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12617
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference9th Symposium on Novel Photoelectronic Detection Technology and Applications
Country/TerritoryChina
CityHefei
Period21/04/2323/04/23

Keywords

  • CG-SL0
  • Compressed sensing
  • Smoothed L0 norm
  • Sparse signal recovery

Fingerprint

Dive into the research topics of 'A reformative algorithm for compressed sensing sparse signal recovery based on smoothed L0 norm'. Together they form a unique fingerprint.

Cite this

Zhang, Y., Chen, X., Zeng, C., Gao, K., & Li, H. (2023). A reformative algorithm for compressed sensing sparse signal recovery based on smoothed L0 norm. In J. Chu, W. Liu, & H. Xu (Eds.), Ninth Symposium on Novel Photoelectronic Detection Technology and Applications Article 126171I (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 12617). SPIE. https://doi.org/10.1117/12.2664402