Bibliographic Metadata

An efficient two-phase L1-TV method for restoring blurred images with impulse noise
AuthorChan, Raymond H. ; Dong, Yiqiu ; Hintermüller, Michael In der Gemeinsamen Normdatei der DNB nachschlagen
Published in
IEEE Transactions on Image Processing, New York, NY, 2010, Vol. 19, Issue 7, page 1731-1739
Document typeJournal Article
Keywords (EN)L1 data fitting / Fenchel duality / image deblurring / impulse noise / noise detector / semismooth Newton method / total variation regularization
Keywords (GND)Bildverarbeitung / Newton-Verfahren / Online-Publikation
URNurn:nbn:at:at-ubg:3-1124 Persistent Identifier (URN)
 The work is publicly available
An efficient two-phase L1-TV method for restoring blurred images with impulse noise [1.26 mb]
Abstract (English)

A two-phase image restoration method based upon total variation regularization combined with an L1-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.