Coherence estimation and speckle filtering based on scattering properties

In this paper, we propose a new speckle filter for polarimetric SAR that preserves pixels´ scattering properties. The basic principle is to select pixels of the same scattering characteristics to be included in the average. To achieve this, the algorithm first applies the Freeman and Durden decomposition to separate pixels into three scattering categories: surface, double bounce and volume, and then unsupervised classification is applied. Speckle filtering is performed using the classification map masks. Pixels centered in a 9×9 window are filtered by including only pixels in the same and two neighboring classes from the same scattering category. This algorithm is extended to the coherence estimation of polarimetric interferometry SAR data. The effectiveness of this new algorithm is demonstrated with JPL AIRSAR and E-SAR data.