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dc.contributor.authorAlanazi, Abdulrahman
dc.contributor.authorBallal, Tarig
dc.contributor.authorMasood, Mudassir
dc.contributor.authorAl-Naffouri, Tareq Y.
dc.date.accessioned2017-11-30T07:06:48Z
dc.date.available2017-11-30T07:06:48Z
dc.date.issued2017-11-02
dc.identifier.citationAlanazi AM, Ballal T, Masood M, Al-Naffouri TY (2017) Image deblurring using a perturbation-based regularization approach. 2017 25th European Signal Processing Conference (EUSIPCO). Available: http://dx.doi.org/10.23919/eusipco.2017.8081637.
dc.identifier.doi10.23919/eusipco.2017.8081637
dc.identifier.urihttp://hdl.handle.net/10754/626255
dc.description.abstractThe image restoration problem deals with images in which information has been degraded by blur or noise. In this work, we present a new method for image deblurring by solving a regularized linear least-squares problem. In the proposed method, a synthetic perturbation matrix with a bounded norm is forced into the discrete ill-conditioned model matrix. This perturbation is added to enhance the singular-value structure of the matrix and hence to provide an improved solution. A method is proposed to find a near-optimal value of the regularization parameter for the proposed approach. To reduce the computational complexity, we present a technique based on the bootstrapping method to estimate the regularization parameter for both low and high-resolution images. Experimental results on the image deblurring problem are presented. Comparisons are made with three benchmark methods and the results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and SSIM values.
dc.description.sponsorshipThis publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. OSR- 2016-KKI-2899.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/8081637/
dc.rights(c) 2017 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.subjectBootstrapping
dc.subjectbounded perturbation regularization
dc.subjectimage deblurring
dc.subjectlinear least-squares problems
dc.subjectTikhonov regularization
dc.titleImage deblurring using a perturbation-basec regularization approach
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journal2017 25th European Signal Processing Conference (EUSIPCO)
dc.eprint.versionPost-print
dc.contributor.institutionKing Saud University (KSU), Riyadh, Saudi Arabia
dc.contributor.institutionKing Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia
kaust.personAlanazi, Abdulrahman
kaust.personBallal, Tarig
kaust.personAl-Naffouri, Tareq Y.
kaust.grant.numberOSR-2016-KKI-2899
refterms.dateFOA2018-06-14T00:05:47Z
dc.date.published-online2017-11-02
dc.date.published-print2017-08


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