An inexact primal–dual method with correction step for a saddle point problem in image debluring
In this paper, we present an inexact primal–dual method with correction step for a saddle point problem by introducing the notations of inexact extended proximal operators with symmetric positive definite matrix D . Relaxing requirement on primal–dual step sizes, we prove the convergence of the prop...
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Veröffentlicht in: | Journal of global optimization 2023-11, Vol.87 (2-4), p.965-988 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
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Zusammenfassung: | In this paper, we present an inexact primal–dual method with correction step for a saddle point problem by introducing the notations of inexact extended proximal operators with symmetric positive definite matrix
D
. Relaxing requirement on primal–dual step sizes, we prove the convergence of the proposed method. We also establish the
O
(1/
N
) convergence rate of our method in the ergodic sense. Moreover, we apply our method to solve TV-
L
1
image deblurring problems. Numerical simulation results illustrate the efficiency of our method. |
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ISSN: | 0925-5001 1573-2916 |
DOI: | 10.1007/s10898-022-01211-6 |