Parallelization of Sparsity-driven Change Detection Method

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dc.contributor.authorOzgur, Atilla
dc.contributor.authorSaran, Ayse Nurdan
dc.contributor.authorNar, Fatih
dc.contributor.orcIDhttps://orcid.org/0000-0002-9237-8347en_US
dc.contributor.researcherIDAAD-6546-2019en_US
dc.date.accessioned2023-06-07T06:37:48Z
dc.date.available2023-06-07T06:37:48Z
dc.date.issued2017
dc.description.abstractIn 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.en_US
dc.identifier.isbn978-1-5090-6494-6en_US
dc.identifier.issn2165-0608en_US
dc.identifier.urihttp://hdl.handle.net/11727/9370
dc.identifier.wos000413813100318en_US
dc.language.isoturen_US
dc.relation.journal2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectChange detectionen_US
dc.subjectsynthetic aperture radaren_US
dc.subjecttotal variationen_US
dc.subjectparallelizationen_US
dc.subjectOpenMPen_US
dc.subjectGPUen_US
dc.subjectCUDAen_US
dc.titleParallelization of Sparsity-driven Change Detection Methoden_US
dc.typeConference Objecten_US

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