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[1] K. Mikula, T. Preußer, and M. Rumpf. Morphological image sequence processing. Computing and Visualization in Science, 6(4):197-209, 2003.
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We present a morphological multi-scale method for image sequence processing, which results in a truly coupled spatio-temporal anisotropic diffusion. The aim of the method is not to smooth the level sets of single frames but to denoise the whole sequence while retaining geometric features such as spatial edges and highly accelerated motions. This is obtained by an anisotropic spatio-temporal level set evolution, where the additional artificial time variable serves as the multi -scale parameter. The diffusion tensor of the evolution depends on the morphology of the sequence, given by spatial curvatures of the level sets and the curvature of trajectories (=acceleration) in sequence-time. We discuss different regularization techniques and describe an operator splitting technique for solving the problem. Finally we compare the new method with existing multi-scale image sequence processing methodologies.