object-oriented and knowledge based classification of polarimetric sar data using polarimetric signature

Optimum Ensemble Classification for Fully Polarimetric SAR Data Using Global-Local Classification Approach

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...

Crop Classification with Multitemporal Polarimetric Sar Data

Multitemporal measurements gathered by EMISAR over the Foulum (Jutland) test site and AirSAR over the Wageningen test site provide an unrivalled opportunity to examine the factors affecting classification of northern European agricultural crops using both polarimetric and multitemporal information. Data analysis, guided by physical principles, has been used to investigate those polarimetric fea...

Model-Based Classification of Polarimetric SAR Sea Ice Data

This paper discusses the role of scattering decomposition models in the classification of polarimetric SAR sea ice data. The iterative Wishart classifier was applied to 3-frequency airborne SAR data acquired in the Beaufort Sea, and the scattering models were found to be helpful in interpreting the assigned classes. In addition to using the full data set, reduced data sets based on an eigenvect...

Classification of polarimetric radar images based on SVM and BGSA

Classification of land cover is one of the most important applications of radar polarimetry images. The purpose of image classification is to classify image pixels into different classes based on vector properties of the extractor. Radar imaging systems provide useful information about ground cover by using a wide range of electromagnetic waves to image the Earthchr('39')s surface. The purpose ...

Stokes Vector Based Polarimetric SAR Land Classification

Iteration Based Polarimetric SAR Image Classification

In this paper, an iteration method is proposed for supervised polarimetric synthetic aperture radar (SAR) image classification. In this iterative approach, the optimization of polarimetric contrast enhancement (OPCE) is employed for enlarging the distance between the mean values of two kinds of targets and the Fisher method is employed for reducing the variances of two distributions. Using the ...