Workshop on

Sparse Tomographic Reconstruction: Theoretical and Numerical Aspects

March 19-20 2015

Abstract: The goal of this workshop is to present state of the art results, on both theoretical guarantees and numerical algorithms, for tomographic reconstruction regularized by co-/sparsity, total variation etc. We aim to pinpoint the gap between the practical efficiency of recent regularization methods, and our mathematical understanding of low complexity models in tomographic inversion. While many theoretical guarantees rely on uniform analysis with random measurements, tomographic reconstruction requires more customized mathematical tools and algorithms to capture the geometry of signals and images that can be stably recovered. This includes for instance total variation minimization from tomographic measurements and the development of novel recovery algorithms that can cope with huge problem sizes like occuring e.g. in 3D tomography. The workshop will gather talks by leading experts in the fields of compressive sensing and large-scale numerical optimization.


Heidelberg Collaboratory for Image Processing (HCI)
University of Heidelberg
Speyerer Strasse 6
69115 Heidelberg (Germany)



Confirmed Speakers

  • Joost K. Batenburg, Centrum Wiskunde & Informatica (CWI) [abstract]
  • Yair Censor, University of Haifa [abstract]
  • Jürgen Frikel, Helmholtz Zentrum München [abstract]
  • Jakob S. Jørgensen, DTU [abstract]
  • Christian Kruschel, University Göttingen [abstract]
  • Martin Kleinsteuber, TUM [abstract]
  • Deanna Needell, Claremont McKenna College [abstract]
  • Marc Nicodème, University of Bordeaux [abstract]
  • Constantin Popa, University of Constanta [abstract]
  • Ioana Pomparau, University of Constanta [abstract]
  • Paul Swoboda, University of Heidelberg [abstract]
  • Andreas Weinmann, Helmholtz Zentrum München [abstract]
  • Eric W. Tramel, Ecole Normale Superieure [abstract]
  • Andreas Tillmann, TU Darmstadt [abstract]
  • Andreas Weinmann, Helmholtz Zentrum München [abstract]

Scientific Organization


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