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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 September 2004en
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.relation.ispartofProceedings of SPIEen
dc.rights© 2004 COPYRIGHT SPIE--The International Society for Optical Engineering.en
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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