Image compressive sensing reconstruction based on collaboration reduced rank preprocessing. Issue 11 (2nd May 2017)

• Record Type: Journal Article
• Authors: Tan, Yun; Hou, Xingsong; Chen, Zan; Yu, Shihang
• Is Part Of: Electronics letters. Volume 53:Issue 11(2017)
• Page Start: 717
• Page End: 718
• Publication Date: 2017-05-02
• Subjects: image reconstruction -- compressed sensing; image compressive sensing reconstruction -- collaboration reduced rank preprocessing -- image CS preprocessing -- image CS reconstruction algorithm -- original image sparsity prior knowledge -- nonlocal sparsity regularisation reconstruction algorithm -- nonlocal low‐rank regularisation reconstruction algorithm -- CRR‐NLR‐CS CS reconstruction method; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2016.3179
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : The problem of image compressive sensing (CS) preprocessing is considered. Currently, image CS reconstruction algorithms mainly consider the sparsity prior knowledge of original image. However, the change of the sparsity strength among the different images may degrade the efficiency of the reconstruction algorithms. Thus the idea of CS preprocessing is proposed to serve two purposes: strengthen the sparsity property of the CS measured image and make preprocessing and reconstruction algorithm matched. Specifically, the collaboration reduced rank (CRR) preprocessing is proposed based on non‐local sparsity and non‐local low‐rank regularisation reconstruction algorithm (NLR‐CS). Then a more efficient CRR‐NLR‐CS CS reconstruction method is proposed which utilises the CRR preprocessing and NLR‐CS. Experimental results show the effectiveness of the proposed method.