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Evaluation of Clustering Performance of Hyperspectral Bands

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dc.contributor.author Haliloğlu, Onur
dc.contributor.author Sakarya, Ufuk
dc.contributor.author Töreyin, Behçet Uğur
dc.date.accessioned 2020-04-19T23:53:56Z
dc.date.available 2020-04-19T23:53:56Z
dc.date.issued 2015
dc.identifier.issn 2165-0608
dc.identifier.uri http://hdl.handle.net/20.500.12416/3382
dc.description.abstract Hyperspectral images have huge data volume that contains spectral and spatial information. This high data volume leads to processing, storage, and transmission problems. Moreover, insufficient training data results in Hughes phenomenon. It is possible to solve these problems with the help of feature selection. In this paper, a method that evaluates the clustering performance of spectral bands is proposed as a pre-processing operation in order to realize feature selection. This method is clustering each spectral band based on "dominant sets" technique and it evaluates the clustering performance of each band. The proposed method is time efficient since it works on a small set of training data instead of the whole hyperspectral data. In this study, "dominant sets" technique is first applied to hyperspectral image processing as a clustering method. tr_TR
dc.language.iso eng tr_TR
dc.publisher IEEE tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Hyperspectral Image Processing tr_TR
dc.subject Dominant Sets tr_TR
dc.subject Clustering tr_TR
dc.title Evaluation of Clustering Performance of Hyperspectral Bands tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal 23nd Signal Processing and Communications Applications Conference (SIU) tr_TR
dc.contributor.authorID 19325 tr_TR
dc.identifier.startpage 2497 tr_TR
dc.identifier.endpage 2500 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümü tr_TR


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