Share Email Print
cover

Proceedings Paper

Characterization of scenarios for multiband and hyperspectral imagers
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

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.

Paper Details

Date Published: 12 April 2004
PDF: 10 pages
Proc. SPIE 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II, (12 April 2004); doi: 10.1117/12.543983
Show Author Affiliations
Jose Manuel Lopez-Alonso, Univ. Complutense de Madrid (Spain)
Javier Alda, Univ. Complutense de Madrid (Spain)


Published in SPIE Proceedings Vol. 5439:
Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II
Harold H. Szu; Mladen V. Wickerhauser; Barak A. Pearlmutter; Wim Sweldens, Editor(s)

© SPIE. Terms of Use
Back to Top