An efficient two-phase L1-TV method for restoring blurred images with impulse noise

Authors:
Raymond H. Chan;Yiqiu Dong;Michael Hintermüller
Affiliations:
Department of Mathematics, The Chinese University of Hong Kong, Shatin, Hong Kong;START-Project "Interfaces and Free Boundaries" and SFB "Mathematical Optimization and Applications in Biomedical Science," Institute of Mathematics and Scientific Computing, University of Graz, Gr ...;START-Project "Interfaces and Free Boundaries" and SFB "Mathematical Optimization and Appl. in Biomed. Sci.," Inst. of Math. and Scientific Comp., Univ. of Graz, Heinrichstrasse, Graz, Austria and ...
Venue:
IEEE Transactions on Image Processing
Year:
2010

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Abstract

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.