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A K-Wishart Markov random field model for clustering of polarimetric SAR imagery
(Peer reviewed; Bokkapittel; Bok; Book; Chapter, 2011-10-20)
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 ...
Bistatic Observations of the Ocean Surface with HF Radar, Satellite and Airborne Receivers
(Peer reviewed; Book; Bok; Bokkapittel; Chapter, 2017-12-25)
A new concept has been developed which can view vast regions of the Earth's surface. Ground HF transmissions are reflected by the ionosphere to illuminate the ocean over a few thousand kilometers. HF receivers detect the radio waves scattered by the sea and land surface. Using the theory of radio wave scatter from ocean surfaces, the HF data is then processed to yield the directional wave-height ...
Deep kernelized autoencoders
(Peer reviewed; Book; Bokkapittel; Bok; Chapter, 2017-05-19)
In this paper we introduce the deep kernelized autoencoder,
a neural network model that allows an explicit approximation of (i) the
mapping from an input space to an arbitrary, user-specified kernel space
and (ii) the back-projection from such a kernel space to input space. The
proposed method is based on traditional autoencoders and is trained
through a new unsupervised loss function. ...