Statistical and phenomenological recognition in polarimetric SAR imaging

Author

Titin-Schnaider, C.

Author_Institution

ONERA, Palaiseau, France

Volume

7

fYear

2001

fDate

2001

Firstpage

3221

Abstract

The maximum likelihood classifiers are of large interest because they allow one to simulate, quantify and compare easily the rate of correct recognition for various cases of partial polarimetries and symmetries hypothesis. In this paper, they are used within the framework of natural surfaces recognition from SAR polarimetric images. The purpose is to advise the choice of the more suitable partial polarimetry for a remote sensing satellite. The results of this work infer some questions about the validity of some properties often supposed in the analysis of SAR images and in the radar calibration method

Keywords

image recognition; radar imaging; radar polarimetry; synthetic aperture radar; SAR image analysis; SAR polarimetric images; maximum Likelihood classifiers; natural surfaces recognition; partial polarimetry; phenomenological recognition; polarimetric SAR imaging; radar calibration method; remote sensing satellite; statistical recognition; symmetries; Calibration; Image analysis; Image recognition; Radar imaging; Radar polarimetry; Radar remote sensing; Remote sensing; Satellites; Spaceborne radar; Synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International

Conference_Location

Sydney, NSW

Print_ISBN

0-7803-7031-7

Type

conf

DOI

10.1109/IGARSS.2001.978309

Filename

978309