Compressive sensing via reweighted TV and nonlocal sparsity regularisation. Issue 3 (1st January 2013)

• Record Type: Journal Article
• Authors: Dong, W.; Yang, X.; Shi, G.
• Is Part Of: Electronics letters. Volume 49:Issue 3(2013)
• Page Start: 184
• Page End: 186
• Publication Date: 2013-01-01
• Subjects: image colour analysis -- image reconstruction -- maximum likelihood estimation -- compressed sensing; nonlocal sparsity regularisation -- total variation regularisation -- TV regularisation -- compressive sensing -- CS reconstruction -- piecewise constant solution -- over‐smoothed image edge -- iteratively reweighted TV regulariser -- spatially adaptive weight -- maximum a posterior estimation -- image gradient -- nonlocal redundancy; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2012.2536
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : Total variation (TV) regularisation has been widely used for compressive sensing (CS) reconstruction. However, since TV regularisers favour piecewise constant solutions, they tend to produce over‐smoothed image edges. To overcome this drawback, proposed is a novel iteratively reweighted TV regulariser for CS reconstruction. Spatially adaptive weights are computed towards a maximum a posteriori estimation of the image gradients. To exploit the nonlocal redundancy, effective nonlocal sparsity regularisation has also been introduced into the proposed objective function. Experimental results demonstrate that the proposed CS reconstruction method outperforms significantly existing TV‐based CS reconstruction methods.