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Iterative Solution Methods

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Handbook of Mathematical Methods in Imaging

Abstract

This chapter deals with iterative methods for nonlinear ill-posed problems. We present gradient and Newton type methods as well as nonstandard iterative algorithms such as Kaczmarz, expectation maximization, and Bregman iterations. Our intention here is to cite convergence results in the sense of regularization and to provide further references to the literature.

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Authors and Affiliations

  1. Institute for Computational and Applied Mathematics, University of Münster, Einsteinstrasse 62, D-48149, Münster, Germany

    Martin Burger

  2. Institut für Mathematik, Alpen-Adria-Universität Klagenfurt, Universitätsstraße 65-67, 9020, Klagenfurt, Austria

    Barbara Kaltenbacher

  3. Industrial Mathematics Institute, Johannes Kepler University Linz, Linz, Austria

    Andreas Neubauer

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  1. Martin Burger
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  2. Barbara Kaltenbacher
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  3. Andreas Neubauer
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Correspondence to Martin Burger .

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  1. Computational Science Center, University of Vienna, Vienna, Austria

    Otmar Scherzer

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Burger, M., Kaltenbacher, B., Neubauer, A. (2015). Iterative Solution Methods. In: Scherzer, O. (eds) Handbook of Mathematical Methods in Imaging. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0790-8_9

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