This paper discusses a multivariate, non-Gaussian para-metric modelling technique to analyse polarimetric SAR data. We investigate a simple class of multivariate non-Gaussian distributions, the 'Scale mixture of Gaussians', and assess its "Goodness-of-fit " to the radar data. Four models are analysed and various characteristics ofthe mod-els are interpreted, together with practical considerations with regard to parameter estimation. We observe that SAR data is often not Gaussian in distribution, being more highly peaked at zero and falling off more slowly than the Gaus-sian. It is shown that a single 'flexible ' model is sufficient to capture the statistics of the SAR data, leading to a fea-ture set ofthe model...
WOSInternational audienceModern SAR systems have high resolution which leads the backscattering clut...
This thesis describes general methods to analyse polarimetric synthetic aperture radar images. The p...
Due to the increasing volume of available SAR Data, powerful classification processings are needed t...
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
iAbstract This thesis discusses a statistical modelling technique to analyse polarimet-ric synthetic...
classier derived from a non-Gaussian model for polarimetric synthetic aperture radar (POLSAR) data. ...
The inadequacy of gaussian statistics in describing certain regions of a synthetic aperture radar (S...
In this paper, two mixture models are proposed for modeling heterogeneous regions in single-look and...
Knowledge of the exact statistical properties of the signal plays an important role in the applicati...
Knowledge of the exact statistical properties of the signal plays an important role in the applicati...
Remote sensing data, and radar data in particular, have become an essential tool for enviromental st...
Abstract—This paper presents an automatic image segmen-tation method for Polarimetric SAR data. It u...
The random walk model is studied with the objective to obtain a physical explanation for the texture...
The inadequacy of gaussian statistics in describing certain regions of a synthetic aperture radar (S...
Synthetic Aperture Radars (SAR) now provide high resolution images of the Earth surface. Traditional...
WOSInternational audienceModern SAR systems have high resolution which leads the backscattering clut...
This thesis describes general methods to analyse polarimetric synthetic aperture radar images. The p...
Due to the increasing volume of available SAR Data, powerful classification processings are needed t...
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
iAbstract This thesis discusses a statistical modelling technique to analyse polarimet-ric synthetic...
classier derived from a non-Gaussian model for polarimetric synthetic aperture radar (POLSAR) data. ...
The inadequacy of gaussian statistics in describing certain regions of a synthetic aperture radar (S...
In this paper, two mixture models are proposed for modeling heterogeneous regions in single-look and...
Knowledge of the exact statistical properties of the signal plays an important role in the applicati...
Knowledge of the exact statistical properties of the signal plays an important role in the applicati...
Remote sensing data, and radar data in particular, have become an essential tool for enviromental st...
Abstract—This paper presents an automatic image segmen-tation method for Polarimetric SAR data. It u...
The random walk model is studied with the objective to obtain a physical explanation for the texture...
The inadequacy of gaussian statistics in describing certain regions of a synthetic aperture radar (S...
Synthetic Aperture Radars (SAR) now provide high resolution images of the Earth surface. Traditional...
WOSInternational audienceModern SAR systems have high resolution which leads the backscattering clut...
This thesis describes general methods to analyse polarimetric synthetic aperture radar images. The p...
Due to the increasing volume of available SAR Data, powerful classification processings are needed t...