Title :
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
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;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2013.2245628