Please use this identifier to cite or link to this item: http://hdl.handle.net/10889/4838
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dc.contributor.authorTsagaris, Vassilisen
dc.contributor.authorPanagiotopoulou, Antigonien
dc.contributor.authorAnastassopoulos, Vassilisen
dc.contributor.otherΤσαγκάρης, Βασίλειοςgr
dc.contributor.otherΠαναγιωτοπούλου, Αντιγόνηgr
dc.contributor.otherΑναστασόπουλος, Βασίλειοςgr
dc.date.accessioned2011-12-08T09:11:47Zen
dc.date.available2011-12-08T09:11:47Zen
dc.date.copyright13-15 September 2004en
dc.date.issued2011-12-08en
dc.identifier.urihttp://hdl.handle.net/10889/4838en
dc.description.abstractA novel procedure which aims in increasing the spatial resolution of multispectral data and simultaneously creates a high quality RGB fused representation is proposed in this paper. For this purpose, neural networks are employed and a successive training procedure is applied in order to incorporate in the network structure knowledge about recovering lost frequencies and thus giving fine resolution output color images. MERIS multispectral data are employed to demonstrate the performance of the proposed method.en
dc.language.isoenen
dc.relation.ispartofProceedings of SPIEen
dc.relation.urihttp://dx.doi.org/10.1117/12.565649en
dc.rights© 2004 COPYRIGHT SPIE--The International Society for Optical Engineering.en
dc.subjectInterpolationen
dc.subjectSuper-resolutionen
dc.subjectMultispectral imagesen
dc.subjectNeural networksen
dc.titleInterpolation in multispectral data using neural networksen
dc.typeConference (paper)en
dcmitype.EventImage and Signal Processing for Remote Sensing Xen
dcterms.extentvol. 5573, no. 10, pp. 460-470en
dcterms.locationGran Canaria, Spainen
Appears in Collections:Τμήμα Φυσικής (Δημοσ. Π.Π. σε συνέδρια)

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