This thesis describes general methods to analyse polarimetric synthetic aperture radar images, with the primary application of unsupervised image segmentation. The fundamental physics of electromagnetic scattering from distributed targets leads to the image phenomenon called speckle. Speckle is shown to be potentially non-Gaussian and several statistical distributions are investigated. Non-Gaussianity ...

This paper will investigate how new developments in remote sensing and sensor technologies can be applied to image the structure of the sea ice surface. Both segmentation of multipolarimetric synthetic aperture radar images and strategies for the analyses of polarimetric SAR data of sea ice are addressed. The analysis is based on a Radarsat 2 PolSAR scene of from the Fram Strait in September ...

A statistical modelling technique is developed to analyse polarimetric synthetic aperture radar (PolSAR) images. Polarimetric SAR data consists of four complex scattering coefficients at each image location, requiring multivariate modelling techniques, and this work focuses on a simple class of multivariate distributions, the scale mixture of Gaussians. Three parametric model families of that ...

In this paper, we propose a new test statistic for unsupervised change detection in polarimetric radar images. We work with multilook complex covariance matrix data, whose underlying model is assumed to be the scaled complex Wishart distribution. We use the complex-kind Hotelling-Lawley trace statistic for measuring the similarity of two covariance matrices. The distribution of the Hotelling-Lawley ...

Radio frequency interference (RFI) is a known issue in low-frequency radar remote sensing. In synthetic aperture radar (SAR) image processing, RFI can cause severe degradation of image quality, distortion of polarimetric signatures, and an increase of the SAR phase noise level. To address this issue, a processing system was developed that is capable of reliably detecting, characterizing, and mitigating ...

This paper proposes a novel unsupervised, non-Gaussian, and contextual segmentation method that combines an advanced statistical distribution with spatial contextual informa-tion for multilook polarimetric synthetic aperture radar (PolSAR)data. This extends on previous studies that have shown the added value of both non-Gaussian modeling and contextual smoothing individually or for intensity channels ...