Change detection in Very High Resolution multisensor optical images

This work aims at developing an approach to the detection of changes in multisensor multitemporal VHR optical images. The main steps of the proposed method are: i) multisensor data homogenization; and ii) change detection in multisensor multitemporal VHR optical images. The proposed approach takes advantage of: the conversion to physical quantities suggested by Pacifici et. Al.1, the framework for the design of systems for change detection in VHR images presented by Bruzzone and Bovolo2 and the framework for unsupervised change detection presented by Bovolo and Bruzzone3. Multisensor data homogenization is achieved during pre-processing by taking into account differences in both radiometric and geometric dimensions. Whereas change detection was approached by extracting proper features from multisensor images such that they result to be comparable (at a given level of abstraction) even if extracted from images acquired by different sensors. In order to illustrate the results, a data set made up of a QuickBird and a WorldView-2 images-acquired in 2006 and 2010 respectively-over an area located in the Trentino region of Italy were used. However, the proposed approach is thought to be exportable to multitemporal images coming from passive sensors other than the two mentioned above. The experimental results obtained on the QuickBird and WorlView-2 image pair are accurate. Thus opening to further experiments on multitemporal images acquired by other sensors.