Distributed Scatterer Processing Based on Binary Partition Trees with Multi-Baseline PolInSAR Data

Distributed scatterers (DSs) are necessary to increase point density in multi-temporal InSAR (MT-InSAR) monitoring. The identification of homogeneous pixels (HPs) is the first and key step for DS processing overcome low signal-to-noise ratio condition. Since multi-polarization data good at describing geometrical structures dielectric properties ground objects, they have been applied HP identification. However, polarimetric information not enough identifying areas with similar objects but different deformation. We propose a novel preprocessing algorithm based on interferometric pixel (PIHP) Firstly, Polarimetric (PolInSAR) similarity that combines intensity, coherence, phase proposed, which readily available multi-baseline flexible by controlling weighting factors. Secondly, binary partition tree (BPT) framework, object-orientated multi-scale PIHP achieved, suitable complex deformation scenes. Tested simulated quad-polarization data, our method shows improvement quality density, especially deformed areas, compared traditional homogeneity (PolHom) test object type map. 30 Radarsat-2 images over Kilauea Volcano, three times higher than PolHom vegetation areas. Our proven be more sensitive mechanically advanced ones, helpful optimization, spatial enlargement monitoring points, stability MT-InSAR algorithm.