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dc.contributor.authorUçar, B.en_US
dc.contributor.authorAykanat, C.en_US
dc.contributor.authorPınar, M. Ç.en_US
dc.contributor.authorMalas, T.en_US
dc.date.accessioned2016-02-08T10:15:37Z
dc.date.available2016-02-08T10:15:37Z
dc.date.issued2007en_US
dc.identifier.issn0743-7315
dc.identifier.urihttp://hdl.handle.net/11693/23552
dc.description.abstractWhen formulated as a system of linear inequalities, the image restoration problem yields huge, unstructured, sparse matrices even for images of small size. To solve the image restoration problem, we use the surrogate constraint methods that can work efficiently for large problems. Among variants of the surrogate constraint method, we consider a basic method performing a single block projection in each step and a coarse-grain parallel version making simultaneous block projections. Using several state-of-the-art partitioning strategies and adopting different communication models, we develop competing parallel implementations of the two methods. The implementations are evaluated based on the per iteration performance and on the overall performance. The experimental results on a PC cluster reveal that the proposed parallelization schemes are quite beneficial.en_US
dc.language.isoEnglishen_US
dc.source.titleJournal of Parallel and Distributed Computingen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.jpdc.2006.10.001en_US
dc.subjectImage restorationen_US
dc.subjectLinear feasibility problemen_US
dc.subjectParallel computingen_US
dc.subjectSurrogate constraint methoden_US
dc.titleParallel image restoration using surrogate constraint methodsen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineering
dc.departmentDepartment of Industrial Engineering
dc.departmentDepartment of Electrical and Electronics Engineering
dc.citation.spage186en_US
dc.citation.epage204en_US
dc.citation.volumeNumber67en_US
dc.citation.issueNumber2en_US
dc.identifier.doi10.1016/j.jpdc.2006.10.001en_US
dc.publisherAcademic Pressen_US
dc.identifier.eissn1096-0848


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