A Multilevel Parcel-Based Approach to Change Detection in Very High Resolution Multitemporal Images

In this paper, we propose a novel parcel-based context-sensitive technique for unsupervised change detection in very high geometrical resolution images. In order to improve pixel-based change-detection performances, we propose to exploit the spatial-context information in the framework of a multilevel approach. The proposed technique models the scene (and hence the changes occurred in the multitemporal data) at different resolution levels, by defining multitemporal and multilevel "parcels" (i.e. small homogeneous regions shared by both original images). Change detection is achieved by applying a specific comparison algorithm to each pixel of the considered images, which properly analyzes the multilevel and multitemporal parcel-based context of the investigated spatial position. The adaptive nature of multitemporal parcels and their multilevel representation allow to properly model complex objects in the investigated scene as well as borders of the changed areas and change details. Expe...