An efficient two-phase L(1)-TV method for restoring blurred images with impulse noise

A two-phase image restoration method based upon total variation regularization combined with an L(1)-data-fitting term for impulse noise removal and deblurring is proposed. In the first phase, suitable noise detectors are used for identifying image pixels contaminated by noise. Then, in the second p...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 19(2010), 7 vom: 01. Juli, Seite 1731-9
1. Verfasser: Chan, Raymond H (VerfasserIn)
Weitere Verfasser: Dong, Yiqiu, Hintermüller, Michael
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2010
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a A two-phase image restoration method based upon total variation regularization combined with an L(1)-data-fitting term for impulse noise removal and deblurring is proposed. In the first phase, suitable noise detectors are used for identifying image pixels contaminated by noise. Then, in the second phase, based upon the information on the location of noise-free pixels, images are deblurred and denoised simultaneously. For efficiency reasons, in the second phase a superlinearly convergent algorithm based upon Fenchel-duality and inexact semismooth Newton techniques is utilized for solving the associated variational problem. Numerical results prove the new method to be a significantly advance over several state-of-the-art techniques with respect to restoration capability and computational efficiency 
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700 1 |a Hintermüller, Michael  |e verfasserin  |4 aut 
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