Title
Unsupervised Classification Based On The Logarithmic Circular Polarization Ratio Parameter For Hybrid Polarimetric Sar
Abstract
In this study, we investigated the unsupervised terrain classification for hybrid polarimetric (HP) SAR by using the circular polarization ratio (CPR) parameter alone. According to the theoretical deduction based on scattering matrices of ideal polarimetric scattering mechanisms (PSMs), CPR is suggested to be processed with the logarithmic function in order to have a balanced span between the ideal PSMs' CPR values, which in turn can improve the identification of real PSMs. Utilizing one simulated HP dataset, the performance of the proposed logarithmic CPR parameter is first compared with that of classical m and chi parameters, and then assessed with real PSM classes identified by the H-alpha classification algorithm. Finally, a simple classification scheme of terrains is proposed and validated.
Year
DOI
Venue
2016
10.1109/IGARSS.2016.7729248
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
Keywords
Field
DocType
Synthetic Aperture Radar, Hybrid Polarimetry, Compact Polarimetry, Terrain Classification
Computer vision,Polarimetry,Circular polarization,Matrix (mathematics),Computer science,Synthetic aperture radar,Terrain,Remote sensing,Artificial intelligence,Polarimetric sar,Scattering,Logarithm
Conference
ISSN
Citations 
PageRank 
2153-6996
0
0.34
References 
Authors
6
5
Name
Order
Citations
PageRank
Shiqiang Chen120.75
Shenglong Guo232.46
Yang Li373.22
Qiang Yin4188.02
HONG Wen577.73