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Modifying the Yamaguchi Four-Component Decomposition Scattering Powers Using a Stochastic Distance

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Title Modifying the Yamaguchi Four-Component Decomposition Scattering Powers Using a Stochastic Distance
 
Creator BHATTACHARYA, A
MUHURI, A
DE, S
MANICKAM, S
FRERY, AC
 
Subject MODEL-BASED DECOMPOSITION
POLARIMETRIC SAR DATA
COHERENCY MATRIX
WISHART DISTRIBUTIONS
POLSAR IMAGERY
CLASSIFICATION
COMPENSATION
POLARIZATION
STATISTICS
TESTS
Polarization orientation angle
radar polarimetry
stochastic distance
synthetic aperture radar (SAR)
 
Description Model-based decompositions have gained considerable attention after the initial work of Freeman and Durden. This decomposition, which assumes the target to be reflection-symmetric, was later relaxed in the Yamaguchi et al. decomposition with the addition of the helix parameter. Since then, many decomposition have been proposed where either the scattering model was modified to fit the data or the coherency matrix representing the second-order statistics of the full polarimetric data is rotated to fit the scattering model. In this paper, we propose to modify the Yamaguchi four-component decomposition (Y4O) scattering powers using the concept of statistical information theory for matrices. In order to achieve this modification, we propose a method to estimate the polarization orientation angle (OA) from full-polarimetric SAR images using the Hellinger distance. In this method, the OA is estimated by maximizing the Hellinger distance between the unrotated and the rotated T33 and the T22 components of the coherency matrix [T]. Then, the powers of the Yamaguchi four-component model-based decomposition (Y4O) are modified using the maximum relative stochastic distance between the T33 and the T22 components of the coherency matrix at the estimated OA. The results show that the overall double-bounce powers over rotated urban areas have significantly improved with the reduction of volume powers. The percentage of pixels with negative powers have also decreased from the Y4O decomposition. The proposed method is both qualitatively and quantitatively compared with the results obtained from the Y4O and the Y4R decompositions for a Radarsat-2 C-band San-Francisco dataset and an UAVSAR L-band Hayward dataset.
 
Publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
 
Date 2016-01-15T08:57:30Z
2016-01-15T08:57:30Z
2015
 
Type Article
 
Identifier IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 8(7SI)3497-3506
1939-1404
2151-1535
http://dx.doi.org/10.1109/JSTARS.2015.2420683
http://dspace.library.iitb.ac.in/jspui/handle/100/18218
 
Language en