ℓ0TV: A new method for image restoration in the presence of impulse noise

Handle URI:
http://hdl.handle.net/10754/556156
Title:
ℓ0TV: A new method for image restoration in the presence of impulse noise
Authors:
Yuan, Ganzhao; Ghanem, Bernard ( 0000-0002-5534-587X )
Abstract:
Total 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.
KAUST Department:
Image and Video Understanding Lab
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Conference/Event name:
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Issue Date:
2-Jun-2015
DOI:
10.1109/CVPR.2015.7299175
Type:
Conference Paper
Sponsors:
IEEE Computer Society, Computer Vision Foundation - CVF
Additional Links:
http://ieeexplore.ieee.org/document/7299175/; https://ivul.kaust.edu.sa/Documents/Publications/2015/L0TV%20%20A%20New%20Method%20for%20Image%20Restoration%20in%20the%20Presence%20of%20Impulse%20Noise.pdf; http://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Yuan_L0TV_A_New_2015_CVPR_paper.html
Appears in Collections:
Conference Papers

Full metadata record

DC FieldValue Language
dc.contributor.authorYuan, Ganzhaoen
dc.contributor.authorGhanem, Bernarden
dc.date.accessioned2015-06-02T13:35:47Zen
dc.date.available2015-06-02T13:35:47Zen
dc.date.issued2015-06-02en
dc.identifier.doi10.1109/CVPR.2015.7299175en
dc.identifier.urihttp://hdl.handle.net/10754/556156en
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.en
dc.description.sponsorshipIEEE Computer Society, Computer Vision Foundation - CVFen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7299175/en
dc.relation.urlhttps://ivul.kaust.edu.sa/Documents/Publications/2015/L0TV%20%20A%20New%20Method%20for%20Image%20Restoration%20in%20the%20Presence%20of%20Impulse%20Noise.pdfen
dc.relation.urlhttp://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Yuan_L0TV_A_New_2015_CVPR_paper.htmlen
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.en
dc.subjectImage Restorationen
dc.subjectSparse Optimizationen
dc.titleℓ0TV: A new method for image restoration in the presence of impulse noiseen
dc.typeConference Paperen
dc.contributor.departmentImage and Video Understanding Laben
dc.identifier.journal2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)en
dc.conference.date07 Jun - 12 Jun 2015en
dc.conference.name2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)en
dc.conference.locationHynes Convention Center 900 Boylston St Boston, MA, USAen
dc.eprint.versionPost-printen
dc.contributor.institutionSouth China University of Technology (SCUT), P.R. Chinaen
kaust.authorGhanem, Bernarden
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