A clustering method that combines an advanced statistical distribution with spatial contextual information is proposed for multilook polarimetric synthetic aperture radar (PolSAR) data. It is based on a Markov random field (MRF) model that integrates a K-Wishart distribution for the PolSAR data statistics conditioned to each image cluster and a Potts model for the spatial context. Specifically, the ...

Non-Gaussian statistical models fit SAR data better than Gaussian-based statistics, in most cases, but are complicated and time-consuming to use for unsupervised image segmentation via probabilistic clustering. The more advanced the model, the more complicated and slow the clustering. The U-distribution has been demonstrated to be one of the most flexible models, capturing the Gaussian/Wishart, the ...

In this paper we propose a new test statistic for unsupervised changedetectioninpolarimetricsyntheticapertureradar(PolSAR) data. We work with multilook complex (MLC) covariance matrix data, whose underlying model is assumed to be the scaled complex Wishart distribution. We use the complex kind Hotelling-Lawley (HL) trace statistic for measuring the similarity of two covariance matrices. The sampling ...

This paper is focused on investigations of the improved correction of the effect of variation in incidence angle on ScanSAR data. Conventional correction methods (such as LLM, locally linear mapping) typically assume that each target class has a similarity distribution in the middle of the image. The objectives of this study are to extend the correction algorithm to full swath width without any ...

This paper introduces a novel unsupervised estimator of equivalent number of looks (ENL) that can be applied to an arbitrary image. It avoids the assumption that homogeneous speckle will dominate the investigated image that is followed by current unsupervised ENL estimators but not always valid, especially for the complex SAR scenes with high mixture and texture. Incorporating the statistical ...

In this paper, a 2-dimensional scattering model for sea ice based on the Finite Element Method (FEM) is presented. The scattering problem is formulated following a physics-separate strategy. The wave in the air domain is expressed by the scattered field formulation, while the wave in the sea ice domain is expressed by the total field formulation. The two separate physics and formulations are coupled ...

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 ...

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 ...

A statistical model for multilook polarimetric radar data is presented where the polarimetric channels are associated with individual texture variables having potentially different statistical properties. The feasibility of producing closed form probability density functions under certain restrictions is outlined. Mellin kind statistics are derived under various assumptions on the texture variables, ...

This work extends upon our simple feature-based multichannel SAR segmentation method to incorporate highly desirable statistical properties into a computationally simple approach. The desirable properties include Markov random field contextual smoothing and goodness-of-fit testing to automatically obtain the significant number of classes. To achieve this we need to find an explicit class model to ...