title: Perturbation-resilient block-iterative projection methods with application to image reconstruction from projections.
abstract: A block-iterative projection algorithm for solving the consistent convex feasibility problem in a finite-dimensional Euclidean space that is resilient to bounded and summable perturbations (in the sense that convergence to a feasible point is retained even if such perturbations are introduced in each iterative step of the algorithm) is proposed. This resilience can be used to steer the iterative process towards a feasible point that is superior in the sense of some functional on the points in the Euclidean space having a small value. The potential usefulness of this is illustrated in image reconstruction from projections, using both total variation and negative entropy as the functional.
authors.affiliation: Department of Computer Science, Graduate Center, City University of New York, New York, NY 10016, USA.
authors.forename: R
authors.initials: R
authors.lastname: Davidi
authors.forename: G T
authors.initials: GT
authors.lastname: Herman
authors.forename: Y
authors.initials: Y
authors.lastname: Censor