A statistical multiresolution strategy for image reconstruction

Authors:
Klaus Frick;Philipp Marnitz
Affiliations:
Institute for Mathematical Stochastics, University of Göttingen, Göttingen, Germany;Institute for Mathematical Stochastics, University of Göttingen, Göttingen, Germany
Venue:
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Year:
2011

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Abstract

In this paper we present a fully data-driven and locally-adaptive method for image reconstruction that is based on the concept of statistical multiresolution estimation as introduced in [1]. It constitutes a statistical regularization technique that uses a ℓ∞ -type distance measure as data fidelity combined with a convex cost functional. The resulting convex optimization problem is approached by a combination of an inexact augmented Lagrangian method and Dykstra's projection algorithm.