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Proceedings Paper

Interpolation in multispectral data using neural networks
Author(s): Vassilis Tsagaris; Antigoni Panagiotopoulou; Vassilis Anastassopoulos
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Paper Abstract

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.

Paper Details

Date Published: 10 November 2004
PDF: 11 pages
Proc. SPIE 5573, Image and Signal Processing for Remote Sensing X, (10 November 2004); doi: 10.1117/12.565649
Show Author Affiliations
Vassilis Tsagaris, Univ. of Patras (Greece)
Antigoni Panagiotopoulou, Univ. of Patras (Greece)
Vassilis Anastassopoulos, Univ. of Patras (Greece)

Published in SPIE Proceedings Vol. 5573:
Image and Signal Processing for Remote Sensing X
Lorenzo Bruzzone, Editor(s)

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