Modified Statistically Homogeneous Pixels’ Selection With Multitemporal SAR Images

Abstract

Statistically homogeneous pixels (SHPs) are considerably significant in many interferometric applications, such as interferometric filtering, distributed scatterer selection, small baseline subset, and SqueeSAR processing. It is very important to achieve SHPs efficiently and accurately. Previous studies on SHPs' selection are based on spatial restrictions and likelihood ratio test, such as Lee filtering, Kolmogorov-Smirnov test, and Anderson-Darling test. However, these algorithms do not stand up to test for the spatial similarity hypothesis for complex terrains with a few images. To solve the problems, this letter proposes a modified SHPs' selection algorithm. It utilizes geometric distance and target features for reaching a priori information to help the similarity hypothesis tests. The proposed algorithm has been tested on simulated and real data to prove the improvements in terms of accuracy and computational efficiency.