ACE-OT: Polarimetric SAR Data-Based Amplitude Contrast Enhancement Algorithm for Offset Tracking Applications

The use of polarimetric synthetic aperture radar (SAR) data can improve the performance of persistent scatterer interferometry (PSI). However, its huge potential remains locked for the amplitude information-based offset tracking (OT) technology. For example, to the best knowledge of the authors, there is no single example of a polarization-based image optimization method that has been developed for OT processing. In this article, an amplitude contrast enhancement (ACE) algorithm is introduced, which demonstrates the potential of the polarimetric SAR data on the improvement of OT performance. Its core idea is finding the optimal combination of the different scattering mechanisms for each pixel to improve the contrast. First, the orientation of the reflected polarization ellipse is removed, to avoid the influence of the geometric relationship between the antenna and the target, and the properties of the target. Then three similarity parameters are defined to represent the three basic reflection types of the single bounce, the double bounce, and the random reflection. After that, the optimizing equation is constructed with two optimizing vectors. Finally, the optimizing vectors are calculated to obtain the enhanced amplitude image. Three examples of the enhancement are presented with different PolSAR images sets of both full- (Radarsat-2) and dual-polarization (TerraSAR-X and Sentinel-1). The performance of ACE-OT has been compared with another method, the adaptive histogram enhancement (AHE). The impact of the number of polarization channels available on ACE-OT performance has also been studied.