A Convex Programming Algorithm for Noisy Discrete Tomography

  • T.D. Capricelli
  • P.L. Combettes
Part of the Applied and Numerical Harmonic Analysis book series (ANHA)


A convex programming approach to discrete tomographic image reconstruction in noisy environments is proposed. Conventional constraints are mixed with noise-based constraints on the sinogram and a binariness-promoting total variation constraint. The noise-based constraints are modeled as confidence regions that are constructed under a Poisson noise assumption. A convex objective is then minimized over the resulting feasibility set via a parallel block-iterative method. Applications to binary tomographic reconstruction are demonstrated.


Image Recovery Poisson Noise Algebraic Reconstruction Technique Discrete Tomography Convex Feasibility Problem 


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Copyright information

© Birkhäuser Boston 2007

Authors and Affiliations

  • T.D. Capricelli
    • 1
  • P.L. Combettes
    • 1
  1. 1.Lab. Jacques-Louis Lions - UMR 7598, Univ. Pierre et Marie Curie - Paris 6ParisFrance

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