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This paper presents a technique for reducing speckle in PolarimetricSynthetic Aperture Radar (PolSAR) imagery using Nonlocal Means and astatistical test based on stochastic divergences. The main objective is toselect homogeneous pixels in the filtering area through statistical testsbetween distributions. This proposal uses the complex Wishart model to describePolSAR data, but the technique can be extended to other models. The weights ofthe location-variant linear filter are function of the p-values of tests whichverify the hypothesis that two samples come from the same distribution and,therefore, can be used to compute a local mean. The test stems from the familyof (h-phi) divergences which originated in Information Theory. This noveltechnique was compared with the Boxcar, Refined Lee and IDAN filters. Imagequality assessment methods on simulated and real data are employed to validatethe performance of this approach. We show that the proposed filter alsoenhances the polarimetric entropy and preserves the scattering information ofthe targets.

Speckle Reduction in Polarimetric SAR Imagery with Stochastic Distances and Nonlocal Means