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dc.contributor.authorTalbi, F.
dc.contributor.authorAlim-Ferhat, F.
dc.contributor.authorSeddiki, S.
dc.contributor.authorHachemi, B.
dc.contributor.editorSkala, Václav
dc.date.accessioned2018-04-16T08:25:00Z-
dc.date.available2018-04-16T08:25:00Z-
dc.date.issued2017
dc.identifier.citationWSCG 2017: poster papers proceedings: 25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 7-11.en
dc.identifier.isbn978-80-86943-46-6
dc.identifier.issn2464-4617
dc.identifier.uriwscg.zcu.cz/WSCG2017/!!_CSRN-2703.pdf
dc.identifier.urihttp://hdl.handle.net/11025/29605
dc.description.abstractThe standard and the directional median filters are effective methods for the removal of impulse-based noise from the images. The main advantage is being the preserving of edges as compared to the mean filter. The main objective of this article is to implement the standard and the directional median filters on FPGA (Field Programmable Gate Array) in order to eliminate impulsive noise in the medical image. As a first step, two algorithms were developed and validated by Matlab tool. Subsequently, two architectures are proposed and implemented using the Xilinx ISE 12.2 environment.en
dc.format5 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.relation.ispartofseriesWSCG 2017: poster papers proceedingsen
dc.rights© Václav Skala - Union Agencycs
dc.subjectimpulsivní šumcs
dc.subjectstřední filtrcs
dc.subjectsměrový střední filtrcs
dc.subjectPSNRcs
dc.subjectFPGAcs
dc.titleEvaluation of standard and directional median filters algorithms and their implementation on FPGA for medical applicationen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedimpulsive noiseen
dc.subject.translatedmedian filteren
dc.subject.translateddirectional median filteren
dc.subject.translatedPSNRen
dc.subject.translatedFPGAen
dc.type.statusPeer-revieweden
Appears in Collections:WSCG 2017: Poster Papers Proceedings

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