The polarimetric decomposition is one of the most important steps in SAR data processing and analyzing. Conventional decomposition methods use polarimetric information only in a restricted number of polarization bases. This paper presents a new decomposition method based on polarimetric signatures. The proposed decomposition includes two main steps: 1) selection of the reference polarimetric signatures, and 2) Classification of the pixel's polarimetric signature. The presented method was tested on the Radarsat-2 image in C band collected over San Francisco and the Pi-SAR image in L band collected over Niigata University in Japan. The proposed decomposition was compared with Y4O, Y4R, Arii-NNED and Freeman decomposition methods. According to the results of the suggested method, in urban areas especially in areas with a large orientation angle, it is clearly seen that the overestimation of the volume contribution has been reduced and the double-bounce contribution has been increased. In addition, the obtained power values of the proposed decomposition
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Maghsoudi, Y., & Taleghani, S. (2017). Polarimetric SAR Data Decomposition Based On Polarimetric Signatures And Reference Scattering Models. Radar, 5(2), 1-14.
MLA
Yaser Maghsoudi; Saeid Taleghani. "Polarimetric SAR Data Decomposition Based On Polarimetric Signatures And Reference Scattering Models", Radar, 5, 2, 2017, 1-14.
HARVARD
Maghsoudi, Y., Taleghani, S. (2017). 'Polarimetric SAR Data Decomposition Based On Polarimetric Signatures And Reference Scattering Models', Radar, 5(2), pp. 1-14.
VANCOUVER
Maghsoudi, Y., Taleghani, S. Polarimetric SAR Data Decomposition Based On Polarimetric Signatures And Reference Scattering Models. Radar, 2017; 5(2): 1-14.