Paper Info
Title
A Three-Component Fisher-Based Feature Weighting Method for Supervised PolSAR Image Classification
Abstract
This letter presents a feature weighting method for polarimetric synthetic aperture radar (PolSAR) image classification. Appropriate feature weighting is essential for obtaining accurate classifications but so far has remained an open research problem. We propose in this letter a supervised three-component feature weighting method based on the Fisher linear discriminant. Fisher linear discriminant method is used to calculate a coefficient for each feature. Then, these coefficients are modified according to a three-component scattering power decomposition model, combining both physical and statistical scattering characteristics to adapt them for the particular scattering mechanisms inherent in PolSAR data and assigned to the coherency matrix to enhance the discriminating ability of the features. Freeman decomposition and Wishart classifier are used to classify the PolSAR image. The effectiveness of the proposed method is demonstrated by experiments NASA/JPL AIRSAR L-band and CSA Radarsat-2 C-band PolSAR images of the San Francisco area.
Year
DOI
Venue
2015
10.1109/LGRS.2014.2360421
IEEE Geosci. Remote Sensing Lett.
Keywords
Field
DocType
feature weighting,synthetic aperture radar,supervised image classification,csa radarsat-2 c-band polsar images,statistical scattering characteristics,three component fisher-based feature weighting method,freeman decomposition,three component scattering power decomposition model,statistical analysis,learning (artificial intelligence),matrix algebra,wishart classifier,fisher linear discriminant method,supervised polsar image classification,polarimetric synthetic aperture radar (polsar),polarimetric synthetic aperture radar,remote sensing by radar,three-component model-based decomposition,feature extraction,image classification,physical characteristics,geophysical image processing,coherency matrix,nasa/jpl airsar l-band images,fisher linear discriminant,radar polarimetry,learning artificial intelligence,matrix decomposition,remote sensing,scattering
Weighting,Matrix (mathematics),Synthetic aperture radar,Remote sensing,Artificial intelligence,Contextual image classification,Classifier (linguistics),Wishart distribution,Computer vision,Pattern recognition,Matrix decomposition,Linear discriminant analysis,Mathematics
Journal
Volume
Issue
ISSN
12
4
1545-598X
Citations 
PageRank 
References 
6
0.45
11
Authors
5
Name
Order
Citations
PageRank
Bo Chen1172.00
Shuang Wang231639.83
L. C. Jiao360726.06
Rustam Stolkin452739.74
Hongying Liu512614.75