A K-Wishart Markov random field model for clustering of polarimetric SAR imagery
A K-Wishart Markov random field model for clustering of polarimetric SAR imagery
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 proposed algorithm is constructed based upon the expectation maximization (EM) algorithm. A new formulation of EM is developed to jointly address parameter estimation in the K-Wishart distribution and the spatial context model, and also minimization of the energy function. Experiments are presented with simulated and real quad-pol L-band data.
- The Arctic University of Norway Norway
- University of Genoa Italy
- Goa University India
VDP::Teknologi: 500::Elektrotekniske fag: 540::Elektronikk: 541, VDP::Mathematics and natural science: 400::Physics: 430::Electromagnetism, acoustics, optics: 434, VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430::Elektromagnetisme, akustikk, optikk: 434, VDP::Technology: 500::Electrotechnical disciplines: 540::Electronics: 541
VDP::Teknologi: 500::Elektrotekniske fag: 540::Elektronikk: 541, VDP::Mathematics and natural science: 400::Physics: 430::Electromagnetism, acoustics, optics: 434, VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430::Elektromagnetisme, akustikk, optikk: 434, VDP::Technology: 500::Electrotechnical disciplines: 540::Electronics: 541
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