Polarimetric SAR image change detection based on low rank and sparse representation with Freeman-Durden decomposition

Abstract

Polarimetric synthetic aperthetic radar(POLAR) is more advanced imaging radar, which includes four channels and provides more information than a single-channel SAR image. However, existing change detection methods cannot make use of polarimetric information from POLSAR data to extract difference image. In this paper, a novel method of change detection based on low rank and sparse decomposition with Freeman-Durden decomposition(FDD) is proposed. The FDD is used to extract scattering features from POLSAR data. Low rank and sparse algorithm is applied to obtain difference information. The results demonstrate the better performance than classical methods for change detection of POLSAR image.