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...
| Κύριοι συγγραφείς: | , , |
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| Άλλοι συγγραφείς: | |
| Μορφή: | Conference (paper) |
| Γλώσσα: | English |
| Έκδοση: |
2011
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| Θέματα: | |
| Διαθέσιμο Online: | http://hdl.handle.net/10889/4838 |
| Περίληψη: | 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. |
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