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It is difficult to extract effective scattering features or describe data using simple statistical distribution for classification of polarimetric SAR. Deep learning is effective in generating complex data model since it use network graph to model data. In this paper, a classification scheme is proposed based on deep learning algorithm, and a hierarchical structure is used to classify data based on...
Polarization ratio and co-polarized phase information are very important for polarimetric synthetic aperture radar (SAR) image interpretation, especially in the area where a single scattering mechanism is dominant. In this study, a new method including both the parameters for scattering characterization is proposed based on the extended Bragg scattering (X-Bragg) model. The theoretical analysis, which...
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