The WGΓ Distribution for Multilook Polarimetric SAR Data and Its Application

Statistical modeling for the statistics of polarimetric synthetic aperture radar (SAR) data is a critical factor in polarimetric SAR data processing. In this letter, we utilize the complex Wishart-generalized Gamma (WG Gamma) distribution to model multilook polarimetric SAR data, in which the complex Wishart distribution and generalized Gamma distribution model the speckle and texture components, respectively. Moreover, we derive a closed-form expression for the WG Gamma distribution based on the product model and propose a parameter estimation technique of the WG Gamma distribution in this letter. We perform the experiments on the polarimetric SAR data acquired by the AIRSAR and ESAR to verify the superiority and effectiveness of the WG Gamma distribution over the K and KummerU distributions in the goodness of fit of polarimetric SAR data histograms and the polarimetric SAR image classification. The experimental results demonstrate that the WG Gamma distribution has a greater flexibility than the K and KummerU distributions in the statistical modeling of multilook polarimetric SAR data.