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Parallelization of sparsity-driven change detection method

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dc.contributor.author Özgür, Atilla
dc.contributor.author Saran, Ayşe Nurdan
dc.contributor.author Nar, Fatih
dc.date.accessioned 2020-02-28T08:06:05Z
dc.date.available 2020-02-28T08:06:05Z
dc.date.issued 2017
dc.identifier.citation Özgür, Atilla; Saran, Ayşe Nurdan; Nar, Fatih, "Parallelization of sparsity-driven change detection method", 2017 25th Signal Processing And Communications Applications Conference (SIU), (2017). tr_TR
dc.identifier.isbn 978-1-5090-6494-6
dc.identifier.uri http://hdl.handle.net/20.500.12416/2545
dc.description.abstract In this study, Sparsity-driven Change Detection (SDCD) method, which has been proposed for detecting changes in multitemporal synthetic aperture radar (SAR) images, is parallelized to reduce the execution time. Parallelization of the SDCD is realized using OpenMP on CPU and CUDA on GPU. Execution speed of the parallelized SDCD is shown on real-world SAR images. Our experimental results show that the computation time of the parallel implementation brings significant speed-ups. tr_TR
dc.language.iso eng tr_TR
dc.publisher IEEE tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Change Detection tr_TR
dc.subject Synthetic Aperture Radar tr_TR
dc.subject Total Variation tr_TR
dc.subject Parallelization tr_TR
dc.subject OpenMP tr_TR
dc.subject GPU tr_TR
dc.subject CUDA tr_TR
dc.title Parallelization of sparsity-driven change detection method tr_TR
dc.type bookPart tr_TR
dc.relation.journal 2017 25th Signal Processing And Communications Applications Conference (SIU) tr_TR
dc.contributor.authorID 20868 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği tr_TR


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