A Multitexture Model for Multilook Polarimetric Synthetic Aperture Radar Data

Abstract

A statistical model for multilook polarimetric radar data is presented where the polarimetric channels are associated with individual texture variables having potentially different statistical properties. The feasibility of producing closed form probability density functions under certain restrictions is outlined. Mellin kind statistics are derived under various assumptions on the texture variables, and the potential for model fit assessment and hypothesis testing in the Mellin domain is demonstrated. Application to real data proves the usefulness of the analytic approach.