Paper
10 November 2004 Interpolation in multispectral data using neural networks
Author Affiliations +
Proceedings Volume 5573, Image and Signal Processing for Remote Sensing X; (2004) https://doi.org/10.1117/12.565649
Event: Remote Sensing, 2004, Maspalomas, Canary Islands, Spain
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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vassilis Tsagaris, Antigoni Panagiotopoulou, and Vassilis Anastassopoulos "Interpolation in multispectral data using neural networks", Proc. SPIE 5573, Image and Signal Processing for Remote Sensing X, (10 November 2004); https://doi.org/10.1117/12.565649
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Image resolution

Neural networks

RGB color model

Image fusion

Lawrencium

Super resolution

Image processing

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