Binary Tomography by Iterating Linear Programs from Noisy Projections

  • Stefan Weber
  • Thomas Schüle
  • Joachim Hornegger
  • Christoph Schnörr
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3322)


In this paper we improve the behavior of a reconstruction algorithm for binary tomography in the presence of noise. This algorithm which has recently been published is derived from a primal-dual subgradient method leading to a sequence of linear programs. The objective function contains a smoothness prior that favors spatially homogeneous solutions and a concave functional gradually enforcing binary solutions. We complement the objective function with a term to cope with noisy projections and evaluate its performance.


Discrete Tomography Combinatorial Optimization Linear Programming D.C. Programming Noise Suppression 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Stefan Weber
    • 1
  • Thomas Schüle
    • 1
    • 3
  • Joachim Hornegger
    • 2
  • Christoph Schnörr
    • 1
  1. 1.Dept. M&CS, CVGPR-GroupUniversity of MannheimMannheimGermany
  2. 2.Erlangen-Nürnberg Dept. CSFriedrich-Alexander UniversityErlangenGermany
  3. 3.Siemens Medical SolutionsForchheimGermany

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