An Efficient Two-Phase L-1-TV Method for Restoring Blurred Images with Impulse Noise
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AbstractA 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.
All Author(s) ListChan RH, Dong YQ, Hintermuller M
Journal nameIEEE Transactions on Image Processing
Year2010
Month7
Day1
Volume Number19
Issue Number7
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1731 - 1739
ISSN1057-7149
eISSN1941-0042
LanguagesEnglish-United Kingdom
KeywordsFenchel duality; image deblurring; impulse noise; L-1 data fitting; noise detector; semismooth Newton method; total variation regularization
Web of Science Subject CategoriesComputer Science; Computer Science, Artificial Intelligence; COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE; Engineering; Engineering, Electrical & Electronic; ENGINEERING, ELECTRICAL & ELECTRONIC

Last updated on 2020-26-09 at 00:03