Optimal classification of polarimetric SAR images using segmentation

Author

Lombardo, Pierfrancesco ; Oliver, Christopher J.

Author_Institution

INFOCOM Dept., Rome Univ., Italy

fYear

2002

fDate

2002

Firstpage

8

Lastpage

13

Abstract

The paper presents an optimised polarimetric segmentation technique for synthetic aperture radar (SAR) images, based on a generalised maximum likelihood approach. A full theoretical derivation is presented, together with a closed form analytical performance evaluation. The technique is compared to other known polarimetric segmentation schemes by application to a polarimetric SAR image of agricultural areas. A complete characterisation of the technique is provided in terms of polarimetric sensitivity and memory requirements.

Keywords

agriculture; image classification; image segmentation; maximum likelihood estimation; optimisation; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; agricultural areas; generalised maximum likelihood approach; optimal classification; optimised polarimetric segmentation technique; polarimetric SAR images; synthetic aperture radar images; Covariance matrix; Image segmentation; Layout; Maximum likelihood estimation; Particle measurements; Performance analysis; Pixel; Reflectivity; Simulated annealing; Synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar Conference, 2002. Proceedings of the IEEE

Print_ISBN

0-7803-7357-X

Type

conf

DOI

10.1109/NRC.2002.999684

Filename

999684