Registration based on evolution models

Image registration is a very common and important problem in several fields such as medical imaging, computer vision, simulation, etc. The aim of this contribution is to present a new mathematical partial differential equation (PDE)-model for the registration of two-dimensional (2D) and three-dimensional (3D), eventually noisy, images. Estimating the registration between two image data sets is here formulated as a motion estimation and evolution problem. Moreover we shortly review the PDE approaches which originated the proposed model. The model is based on ideas introduced for processing of space-time image sequences. The proposed algorithm can deal with small and large deformations, it also works in presence of noise and it is very fast. Computational results in processing of a variety of images including synthetic and medical images are presented.