A K-Wishart Markov random field model for clustering of polarimetric SAR imagery

Citation

Akbari V, Moser G, Doulgeris AP, Anfinsen SN, Eltoft T & Serpico SB (2011) A K-Wishart Markov random field model for clustering of polarimetric SAR imagery. In: IGARSS 2011 - 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada, 24.07.2011-29.07.2011. New Jersey: IEEE. https://doi.org/10.1109/igarss.2011.6049317

Abstract
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.

People

Dr Vahid Akbari

Lect in Artificial Intelligence/Data Sci, Computing Science and Mathematics - Division