Interpolation in multispectral data using neural networks
A 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...
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2011
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| Online Access: | http://hdl.handle.net/10889/4838 |
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nemertes-10889-48382022-09-05T13:58:20Z Interpolation in multispectral data using neural networks Tsagaris, Vassilis Panagiotopoulou, Antigoni Anastassopoulos, Vassilis Τσαγκάρης, Βασίλειος Παναγιωτοπούλου, Αντιγόνη Αναστασόπουλος, Βασίλειος Interpolation Super-resolution Multispectral images Neural networks A 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. 2011-12-08T09:11:47Z 2011-12-08T09:11:47Z 13-15 September 2004 2011-12-08 Conference (paper) http://hdl.handle.net/10889/4838 en Proceedings of SPIE http://dx.doi.org/10.1117/12.565649 © 2004 COPYRIGHT SPIE--The International Society for Optical Engineering. application/pdf |
| institution |
UPatras |
| collection |
Nemertes |
| language |
English |
| topic |
Interpolation Super-resolution Multispectral images Neural networks |
| spellingShingle |
Interpolation Super-resolution Multispectral images Neural networks Tsagaris, Vassilis Panagiotopoulou, Antigoni Anastassopoulos, Vassilis Interpolation in multispectral data using neural networks |
| description |
A 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. |
| author2 |
Τσαγκάρης, Βασίλειος |
| author_facet |
Τσαγκάρης, Βασίλειος Tsagaris, Vassilis Panagiotopoulou, Antigoni Anastassopoulos, Vassilis |
| format |
Conference (paper) |
| author |
Tsagaris, Vassilis Panagiotopoulou, Antigoni Anastassopoulos, Vassilis |
| author_sort |
Tsagaris, Vassilis |
| title |
Interpolation in multispectral data using neural networks |
| title_short |
Interpolation in multispectral data using neural networks |
| title_full |
Interpolation in multispectral data using neural networks |
| title_fullStr |
Interpolation in multispectral data using neural networks |
| title_full_unstemmed |
Interpolation in multispectral data using neural networks |
| title_sort |
interpolation in multispectral data using neural networks |
| publishDate |
2011 |
| url |
http://hdl.handle.net/10889/4838 |
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AT tsagarisvassilis interpolationinmultispectraldatausingneuralnetworks AT panagiotopoulouantigoni interpolationinmultispectraldatausingneuralnetworks AT anastassopoulosvassilis interpolationinmultispectraldatausingneuralnetworks |
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1771297245949329408 |
