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Nonmonotone and Monotone Active-Set Methods for Image Restoration, Part 1: Convergence Analysis

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  • T. KÄRKKÄINEN

    (University of Jyväskylä)

  • K. Majava

    (University of Jyväskylä)

Abstract

Active-set methods based on augmented Lagrangian smoothing of nondifferentiable optimization problems arising in image restoration are discussed. One-dimensional image restoration problems and two different formulations of two-dimensional image restoration problems are given. Both nonmonotone and monotone active-set algorithms are described and finite-step convergence of the algorithms is considered.

Suggested Citation

  • T. KÄRKKÄINEN & K. Majava, 2000. "Nonmonotone and Monotone Active-Set Methods for Image Restoration, Part 1: Convergence Analysis," Journal of Optimization Theory and Applications, Springer, vol. 106(1), pages 61-80, July.
    • Handle: RePEc:spr:joptap:v:106:y:2000:i:1:d:10.1023_a:1004655007088
    DOI: 10.1023/A:1004655007088
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    1. T. KÄRKKÄINEN & K. Majava, 2000. "Nonmonotone and Monotone Active-Set Methods for Image Restoration, Part 2: Numerical Results," Journal of Optimization Theory and Applications, Springer, vol. 106(1), pages 81-105, July.
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    1. T. KÄRKKÄINEN & K. Majava, 2000. "Nonmonotone and Monotone Active-Set Methods for Image Restoration, Part 2: Numerical Results," Journal of Optimization Theory and Applications, Springer, vol. 106(1), pages 81-105, July.

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