An Approach to Change Detection in Time series of SAR Images Based on Multitemporal Similarity Measures

This work deals with a novel adaptive parcel-based method for change detection in long time series of SAR images. The proposed technique considers two temporal series of SAR images acquired over the same geographical area in different periods and is based on the following 3 steps: a) adaptive modeling of the geometry of multitemporal SAR sequences according to the generation of spatio-temporal homogeneous regions (i.e., spatio-temporal parcels); b) comparison of series according to a parcel-based similarity measure (e.g., the Kullback-Leibler distance); and c) change-detection map generation according to thresholding. Parcels result in a proper modeling of complex spatial-temporal phenomena in the scene as well as borders and details of the changed areas. The use of similarity measures between long temporal series allows one capturing the complexity of multitemporal data involving statistics of different order. Experiments carried out on two sequences of ERS-1/ERS-2 SAR data confirmed ...