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dc.contributor.authorYuan, Ganzhao
dc.contributor.authorGhanem, Bernard
dc.date.accessioned2015-06-02T13:35:47Z
dc.date.available2015-06-02T13:35:47Z
dc.date.issued2015-06-02
dc.identifier.doi10.1109/CVPR.2015.7299175
dc.identifier.urihttp://hdl.handle.net/10754/556156
dc.description.abstractTotal Variation (TV) is an effective and popular prior model in the field of regularization-based image processing. This paper focuses on TV for image restoration in the presence of impulse noise. This type of noise frequently arises in data acquisition and transmission due to many reasons, e.g. a faulty sensor or analog-to-digital converter errors. Removing this noise is an important task in image restoration. State-of-the-art methods such as Adaptive Outlier Pursuit(AOP), which is based on TV with L02-norm data fidelity, only give sub-optimal performance. In this paper, we propose a new method, called L0T V -PADMM, which solves the TV-based restoration problem with L0-norm data fidelity. To effectively deal with the resulting non-convex nonsmooth optimization problem, we first reformulate it as an equivalent MPEC (Mathematical Program with Equilibrium Constraints), and then solve it using a proximal Alternating Direction Method of Multipliers (PADMM). Our L0TV-PADMM method finds a desirable solution to the original L0-norm optimization problem and is proven to be convergent under mild conditions. We apply L0TV-PADMM to the problems of image denoising and deblurring in the presence of impulse noise. Our extensive experiments demonstrate that L0TV-PADMM outperforms state-of-the-art image restoration methods.
dc.description.sponsorshipIEEE Computer Society, Computer Vision Foundation - CVF
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/7299175/
dc.relation.urlhttps://ivul.kaust.edu.sa/Documents/Publications/2015/L0TV%20%20A%20New%20Method%20for%20Image%20Restoration%20in%20the%20Presence%20of%20Impulse%20Noise.pdf
dc.relation.urlhttp://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Yuan_L0TV_A_New_2015_CVPR_paper.html
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.subjectImage Restoration
dc.subjectSparse Optimization
dc.titleℓ0TV: A new method for image restoration in the presence of impulse noise
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentVisual Computing Center (VCC)
dc.contributor.departmentImage and Video Understanding Lab
dc.identifier.journal2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
dc.conference.date07 Jun - 12 Jun 2015
dc.conference.name2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
dc.conference.locationHynes Convention Center 900 Boylston St Boston, MA, USA
dc.eprint.versionPost-print
dc.contributor.institutionSouth China University of Technology (SCUT), P.R. China
kaust.personGhanem, Bernard
refterms.dateFOA2018-06-14T07:12:31Z


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