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Tomographic imaging from limited projections is an ill-posed problem and reconstruction algorithms rely on regularization, often sparsity-based, to improve the quality of imaging. We present a spline framework for consistent discretization in tomographic reconstruction and demonstrate its advantages for sparse approximation. Our experiments provide comparisons with commonly-used techniques such as total variation based tomographic reconstruction.
This presentation is part of Minisymposium “MS47 - Splines in Imaging (3 parts)”
organized by: Carolina Beccari (Dept. Mathematics, University of Bologna) , Virginie Uhlmann (EPFL, Lausanne) , Michael Unser (EPFL, Lausanne) .