Linearized proximal alternating minimization algorithm for motion deblurring by nonlocal regularization

Non-blind motion deblurring problems are highly ill-posed and so it is quite difficult to find the original sharp and clean image. To handle ill-posedness of the motion deblurring problem, we use nonlocal total variation (abbreviated as TV) regularization approaches. Nonlocal TV can restore periodic...

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Bibliographic Details
Published in:	Pattern recognition Vol. 44; no. 6; pp. 1312 - 1326
Main Authors:	Yun, Sangwoon, Woo, Hyenkyun
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01.06.2011 Elsevier
Subjects:	Algorithms Alternating minimization Applied sciences Convex optimization Deconvolution Exact sciences and technology Image processing Information, signal and communications theory Mathematical models Motion deblurring Nonlocal Operators Regularization Signal processing State of the art Telecommunications and information theory Television Texture Total variation Deconvolution Nonlocal Convex optimization Total variation Alternating minimization Regularization Motion deblurring Performance evaluation State of the art Image processing Image restoration Algorithm Blurred image Convex programming Texture Television Numerical simulation Ill posed problem Linearization
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
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