Classification Method for Fully PolSAR Data Based on Three Novel Parameters

Author

Shuang Zhang ; Shuang Wang ; Bo Chen ; Shasha Mao

Author_Institution

Key Lab. of Intell. Perception & Image Understanding, Xi´an, China

Volume

11

Issue

1

fYear

2014

fDate

Jan. 2014

Firstpage

39

Lastpage

43

Abstract

In this letter, a new classification method for fully polarimetric synthetic aperture radar (PolSAR) data based on three novel parameters is presented. The three parameters are derived from the eigenspace of the coherency matrix as linear combinations of its three eigenvalues. In the proposed classification method, the maximum value out of the three parameters is determined to assign a label to each image pixel, and the PolSAR image is classified into three classes accordingly. Experimental results based on NASA/JPL AIRSAR L-band data and CSA RADARSAT-2 C-band data illustrate the validity and efficacy of the procedure.

Keywords

eigenvalues and eigenfunctions; image classification; matrix algebra; radar imaging; radar polarimetry; synthetic aperture radar; CSA RADARSAT-2 C-band data; NASA-JPL AIRSAR L-band data; coherency matrix eigenspace; eigenvalue; fully PolSAR data classification method; image classification; polarimetric synthetic aperture radar; Image classification; radar polarimetry; scattering mechanism; target decomposition;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2013.2245628

Filename

6487379