Nonmonotone and monotone active-set method for image restoration. I: Convergence analysis.
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Publication:1586816
DOI10.1023/A:1004655007088zbMath1050.90032OpenAlexW92521872WikidataQ109967926 ScholiaQ109967926MaRDI QIDQ1586816
Publication date: 6 March 2001
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1023/a:1004655007088
Applications of mathematical programming (90C90) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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Cites Work
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- Nonlinear total variation based noise removal algorithms
- Regularization by functions of bounded variation and applications to image enhancement
- Image recovery via total variation minimization and related problems
- Augmented Lagrangian methods for nonsmooth, convex optimization in Hilbert spaces
- Nonmonotone and monotone active-set methods for image restoration. II: Numerical results.
- On the method of multipliers for mathematical programming problems
- An active set strategy based on the augmented Lagrangian formulation for image restoration
- Convergence of an Iterative Method for Total Variation Denoising
- A Variational Method in Image Recovery
- Regularization of linear least squares problems by total bounded variation
- Analysis of regularized total variation penalty methods for denoising
- Recovery of Blocky Images from Noisy and Blurred Data
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