A Convex Programming Algorithm for Noisy Discrete Tomography
作者： T.D. Capricelli , P.L. Combettes
DOI: 10.1007/978-0-8176-4543-4_10
关键词:
摘要: A convex programming approach to discrete tomographic image reconstruction in noisy environments is proposed. Conventional constraints are mixed with noise-based on the sinogram and a binariness-promoting total variation constraint. The modeled as confidence regions that constructed under Poisson noise assumption. objective then minimized over resulting feasibility set via parallel block-iterative method. Applications binary demonstrated.
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