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• W1585966427 abstract "We propose a new splitting approach for the Potts model (also called piecewise constant Mumford-Shah model) for inverse imaging problems. The Potts model is an optimization problem of a cost function which forces a sparse gradient. Since the cost function is highly non-convex its minimization is a challenging problem. We here propose a discrete domain splitting based on the alternating direction method of multipliers (ADMM). Our scheme allows for arbitrarily close approximations to an isotropic discretization and thus avoids anisotropy effects like geometric staircasing. We show the capability of our method for the reconstruction of Radon data and spherical Radon data, which are the models for classical computed tomography and photo acoustic tomography, respectively. Our approach is particularly suitable for limited data setups such as sparse angle tomography. For example, our method is able to reconstruct the Shepp-Logan phantom from only 7 projections of Radon data as well as from 7 projections of spherical Radon data. We demonstrate the practical applicability of our approach in an experiment with real PET data." @default.
• W1585966427 created "2016-06-24" @default.
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• W1585966427 date "2014-05-22" @default.
• W1585966427 modified "2023-10-01" @default.
• W1585966427 title "A splitting approach to Potts regularization of inverse imaging problems" @default.
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• W1585966427 hasPublicationYear "2014" @default.
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