A Convex Programming Algorithm for Noisy Discrete Tomography

نویسندگان

  • T. D. Capricelli
  • P. L. Combettes
چکیده

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 binarity-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.

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تاریخ انتشار 2007