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12 April 2004 Characterization of scenarios for multiband and hyperspectral imagers
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The number of imager devices using multiband or hyperspectral scenes has increased in recent years. For surveillance, or even remote sensing applications, it is necessary to reduce the amount of collected information in order to be useful for automatic or human classification tasks, with affordable performance. In this sense it is very important to filter out only redundant information still preserving the relevant information. In this paper we present an approach in order to compact this information based on a multivariate statistical analysis of spectrums that uses an automatized principal component analysis. Possible applications and use for imagers using color outputs are also given.
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Jose Manuel Lopez-Alonso and Javier Alda "Characterization of scenarios for multiband and hyperspectral imagers", Proc. SPIE 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II, (12 April 2004);

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