Revising regularisation with linear approximation term for compressive sensing improvement

Zan Chen, Xingsong Hou, Ling Shao, Shidong Wang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
10 Downloads (Pure)


In this Letter, the authors propose a novel revised regularisation to improve the performance of compressive sensing (CS) reconstruction. They suppose that a specific regularisation term is insufficient to accommodate the prior information of CS while it can be improved by further imposing a linear approximation term. They also prove that the revised regularisation is substantially equivalent to the CS preprocessing methods. They conduct extensive experiments on various CS algorithms, which show the effectiveness of their revised regularisation.

Original languageEnglish
Pages (from-to)384-386
Number of pages3
JournalElectronics Letters
Issue number7
Early online date13 Feb 2019
Publication statusPublished - 4 Apr 2019

Cite this