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Noise-reducing cascadic multilevel methods for linear discrete ill-posed problems

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Abstract

Cascadic multilevel methods for the solution of linear discrete ill-posed problems with noise-reducing restriction and prolongation operators recently have been developed for the restoration of blur- and noise-contaminated images. This is a particular ill-posed problem. The multilevel methods were found to determine accurate restorations with fairly little computational work. This paper describes noise-reducing multilevel methods for the solution of general linear discrete ill-posed problems.

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Authors and Affiliations

  1. Department of Math.-CIRAM, University of Bologna, Piazza Porta S. Donato 5, 40126, Bologna, Italy

    S. Morigi & F. Sgallari

  2. Department of Mathematical Sciences, Kent State University, Kent, OH, 44242, USA

    L. Reichel

Authors
  1. S. Morigi
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  2. L. Reichel
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  3. F. Sgallari
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Correspondence to L. Reichel.

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Morigi, S., Reichel, L. & Sgallari, F. Noise-reducing cascadic multilevel methods for linear discrete ill-posed problems. Numer Algor 53, 1–22 (2010). https://doi.org/10.1007/s11075-009-9282-3

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  • DOI: https://doi.org/10.1007/s11075-009-9282-3

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