Spatial Adaptive Speckle Filtering Driven by Temporal Polarimetric Statistics and Its Application to PSI

Persistent scatterer (PS) interferometry (PSI) techniques are designed to measure ground deformations using satellite synthetic aperture radar (SAR) data. They rely on the identification of pixels not severely affected by spatial or temporal decorrelation, which, in general, correspond to pointlike PSs commonly found in urban areas. However, in urban areas, we can find not only PSs but also distributed scatterers (DSs) whose phase information may be exploited for PSI applications. Estimation of DS parameters requires speckle filtering to be applied to the complex SAR data, but conventional speckle filtering approaches tend to mask PS information due to spatial averaging. In the context of single-polarization PSI, adaptive speckle filtering strategies based on the exploitation of amplitude temporal statistics have been proposed, which seek to avoid spatial filtering on nonhomogeneous areas. Given the growing interest on polarimetric PSI techniques, i.e., those using polarimetric diversity to increase performance over conventional single-polarization PSI, in this paper, we propose an adaptive spatial filter driven by polarimetric temporal statistics, rather than single-polarization amplitudes. The proposed approach is able to filter DS while preserving PS information. In addition, a new methodology for the joint processing of PS and DS in the context of PSI is introduced. The technique has been tested for two different urban data sets: 41 dual-polarization TerraSAR-X images of Murcia (Spain) and 31 full-polarization Radarsat-2 images of Barcelona (Spain). Results show an important improvement in terms of number of pixels with valid deformation information, hence denser area coverage.