Parallel Block-Iterative Reconstruction Algorithms for Binary Tomography

Abstract A convex programming approach to binary tomographic image reconstruction in noisy environments is proposed. Conventional constraints are mixed with new constraints on the sinogram. A convex objective is then minimized over the resulting feasibility set via a parallel block-iterative method. The new constraints involve noise-based confidence regions and a binarity-promoting total variation constraint.

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