Perturbation-resilient block-iterative projection methods with application to image reconstruction from projections

R. Davidi, G. T. Herman, Y. Censor

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)505-524
Number of pages20
JournalInternational Transactions in Operational Research
Volume16
Issue number4
DOIs
StatePublished - Jul 2009

Keywords

  • Block-iterative algorithms
  • Convex feasibility
  • Image reconstruction
  • Perturbation resilience
  • Product space
  • Projection methods
  • Superiorization

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Business and International Management
  • Computer Science Applications
  • Strategy and Management
  • Management Science and Operations Research

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