Classification of earth terrain in polarimetric SAR images using neural nets modelization

Eric Pottier; Joseph Saillard

doi:10.1117/12.140624

12 February 1993 Classification of earth terrain in polarimetric SAR images using neural nets modelization

Eric Pottier, Joseph Saillard

Proceedings Volume 1748, Radar Polarimetry; (1993) https://doi.org/10.1117/12.140624
Event: San Diego '92, 1992, San Diego, CA, United States

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.

Citation Download Citation

Eric Pottier and Joseph Saillard "Classification of earth terrain in polarimetric SAR images using neural nets modelization", Proc. SPIE 1748, Radar Polarimetry, (12 February 1993); https://doi.org/10.1117/12.140624

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