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Proceedings Paper

Classification of earth terrain in polarimetric SAR images using neural nets modelization
Author(s): Eric Pottier; Joseph Saillard
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Paper Abstract

Two supervised classification procedures are presented and applied to relative polarimetric SAR images in order to identify the different Earth terrain components. The first one is the classical Bayes classifier, and the second is an original polarimetric method based on a neural network modelization. The subject of this paper is to show that it is possible to classify polarimetric data by using neural network techniques, without knowing the a-priori statistic distributions of the different classes. The purpose being to show that POLARIMETRY and IA theories can become complementary sciences.

Paper Details

Date Published: 12 February 1993
PDF: 12 pages
Proc. SPIE 1748, Radar Polarimetry, (12 February 1993); doi: 10.1117/12.140624
Show Author Affiliations
Eric Pottier, IRESTE/Univ. of Nantes (France)
Joseph Saillard, IRESTE/Univ. of Nantes (France)

Published in SPIE Proceedings Vol. 1748:
Radar Polarimetry
Harold Mott; Wolfgang-Martin Boerner, Editor(s)

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