Classification of Fully Polarimetric SAR Image Based on Polarimetric Target Decomposition and Wishart Markov Random Field

A new classification method is proposed for polarimetric SAR images.The H/Alpha/A decomposition is combined with Markov random field model.Firstly,H/Alpha/A decomposition is adopted to obtain 16 initial clusters based on their scattering characteristics.Secondly,the wishart distribution based on maximum likelihood is implied to update the classification result.Finally,by the adoption of wishart Markov random field model,iterated conditional model method(ICM) based on maximum a posteriori criterion is used to acquire the final classification result.Using fully polarimetric SAR images acquired by the NASA/ JPL,the experimental results verify the effectiveness of this improved algorithm.