Change Detection of Multi-polarimetric Sar Data Based on Principal Component Analysis

Recently, Polarimetric SAR (PolSAR) techniques have been much studied as hot research topics in the area of SAR. The objective of this paper is to assess the Principal component analysis (PCA) technique combining with multi-polarimetric SAR data for change detection. PCA proposed in this paper give an effective and quick way to achieve the difference map from the whole multi-temporal images, and while the multi-polarimetric SAR present more information than traditional single-polarimetric SAR and can give an accurate result for change detection. Finally, the simulated multi-temporal SAR images from ERS are used to validate the PCA technique, and then ENVISAT dual-pol SAR data and ALOS PALSAR full-pol SAR data are applied to present the preliminary results of change detection. The results show that the polarimetric PCA technique proposed here has a good performance on those experimental SAR data, because it take full advantage of two components corresponding to unchanged and changed portion and the polarimetric information.