In this paper, a proposed ensemble classification for fully polarimetric synthetic aperture radar (PolSAR) data using a global-local classification approach is presented. In the first step, to perform the global classification, the training feature space is divided into a specified number of clusters. In the next step to carry out the local classification over each of these clusters, which cont...

in this paper, an unsupervised classification method using spatial contextual information for polarimetric sar (polsar) image classification is proposed. first, an unsupervised classification based on 2d h/▁α plane was performed, using cloude/pottier target decomposition algorithm. in order to compute the initial values of the cluster centers and hence a rapid convergence of the algorithm, the ...

This work investigates the parallel implementation of polarimetric synthetic aperture radar (POLSAR) data processing chain. Such processing can be computationally expensive when large data sets are processed. However, the processing steps can be largely implemented in a high performance computing (HPC) environment. In this work, we studied different aspects of the computations involved in proce...

During the last decade, multi-frequency and polarimetric SAR (PolSAR) imaging has been investigated with respect to classification of terrain types, many supervised and unsupervised segmentation and classification methods for PolSAR data have been proposed. However, it is still very difficult to get a reliable and consistent scene semantic segmentation for PolSAR imagery. Recently, with the int...

In the context of non-Gaussian polarimetric clutter models, this paper presents an application of the recent advances in the field of Spherically Invariant Random Vectors (SIRV) modelling for coherency matrix estimation in heterogeneous clutter. The complete description of the POLSAR data set is achieved by estimating the span and the normalized coherency independently. The normalized coherency...

This paper examines seasonal change of the water area in Lake Sakata by using Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. Statistical POLSAR image analysis is carried out for both Xand L-band data, based on a threecomponent scattering power decomposition method, where the decomposed components are surface scattering, doublebounce scattering and volume scattering components. F...

In recent decades, most methods proposed for radiometric slope correction involved the backscattering intensity values in synthetic aperture radar (SAR) data. However, these methods are not fully applicable to quad-polarimetric SAR (PolSAR) matrix data. In this paper, we propose a three-step semi-empirical radiometric terrain correction approach for PolSAR forest area data. The three steps of t...

Polarimetric Synthetic Aperture Radar (PolSAR) sensors can transmit and receive electromagnetic waves in different polarization states. As a result, PolSAR images are complex multi-dimensional data which can be extensively applied in sea ice monitoring and classification. The discrimination capability of PolSAR data makes them a unique source of information with a significant contribution to ma...

Because of the low signal-to-clutter ratio, it is a difficult problem to detect and image moving targets in foliage. In this paper, a multifrequency multiaperture polarimetric synthetic aperture radar (MFMA POLSAR) system is proposed for imaging of moving targets in foliage. The MFMA POLSAR extends the multifrequency antenna array SAR (MF-SAR) system to multiple polarizations. Full polarization...

In this paper the most significant and recent polarimetric SAR (PolSAR) speckle filters that have been developed so far are reviewed and the effects of them on classification and their ability to preserve polarimetric properties along with their strength in noise reduction are studied. For this purpose, the PolSAR filters such as refined Lee, intensity driven adaptive neighborhood (IDAN), scatt...