Morphological image sequence processing

Authors:
Karol Mikula;Tobias Preusser;Martin Rumpf
Affiliations:
Slovak University of Technology, Department of Mathematics, Slovakia;Duisburg University, Fakulty 4, Institute for Mathematics, Germany;Duisburg University, Fakulty 4, Institute for Mathematics, Germany
Venue:
Computing and Visualization in Science
Year:
2004

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Abstract

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.