DocumentCode
1177901
Title
Deorientation theory of polarimetric scattering targets and application to terrain surface classification
Author
Xu, Feng ; Jin, Ya-Qiu
Author_Institution
Key Lab. of Wave Scattering & Remote Sensing Inf., Fudan Univ., Shanghai, China
Volume
43
Issue
10
fYear
2005
Firstpage
2351
Lastpage
2364
Abstract
Deorientation theory of polarimetric scattering targets is presented. Using a transformation of the target scattering vector, the target orientation is turned to a certain fixed state and polarimetric scattering of the transformed scattering vector shows the prominence of the generic characteristics of the target. A new set of parameters u, v, w, ψ is defined based on a deorientation of the target scattering vector. Numerical simulation of polarimetric scattering of nonspherical particles illustrates the meanings of the parameters u, v, w, ψ and the entropy H. An unsupervised classification scheme of the terrain surfaces is developed, which classifies the terrain surfaces using the set of u., v, H, and analyzes the orientation distribution of each class based on deorientation angle ψ. As examples, a SIR-C polarimetric image over China´s Guangdong Hui-Yang district is classified into eight classes and a AirSAR polarimetric image over Canada´s Boreal district is orientation-analyzed using our approach of deorientation and four parameters u, v, ψ, and H.
Keywords
image classification; radar polarimetry; remote sensing by radar; synthetic aperture radar; terrain mapping; AirSAR; Boreal district; Canada; China; Guangdong Hui-Yang district; deorientation theory; entropy; polarimetric scattering; synthetic aperture radar; target orientation; target scattering; terrain surface classification; unsupervised classification; Entropy; Numerical simulation; Optical scattering; Optical surface waves; Particle scattering; Polarimetric synthetic aperture radar; Radar scattering; Remote sensing; Scattering parameters; Synthetic aperture radar; Deorientation; polarimetric synthetic aperture radar (SAR); unsupervised classification;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/TGRS.2005.855064
Filename
1512406
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