Simultaneous registration, segmentation and change detection from multisensor, multitemporal satellite image pairs
In this paper, a novel generic framework has been designed, developed and validated for addressing simultaneously the tasks of image registration, segmentation and change detection from multisensor, multiresolution, multitemporal satellite image pairs. Our approach models the inter-dependencies of variables through a higher order graph. The proposed formulation is modular with respect to the nature of images (various similarity metrics can be considered), the nature of deformations (arbitrary interpolation strategies), and the nature of segmentation likelihoods (various classification approaches can be employed). Inference of the proposed formulation is achieved through its mapping to an overparametrized pairwise graph which is then optimized using linear programming. Experimental results and the performed quantitative evaluation indicate the high potentials of the developed method.