Adaptive Arnoldi-Tikhonov regularization for image restoration

DOI10.1007/s11075-013-9712-0zbMath1298.65071OpenAlexW2129608496MaRDI QIDQ457035

Paolo Novati, Maria Rosaria Russo

Publication date: 26 September 2014

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11075-013-9712-0

zbMATH Keywords

Tikhonov regularizationnumerical experimentArnoldi algorithmKrylov methodsimage restorationlinear discrete ill-posed problem

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (5)

Embedded techniques for choosing the parameter in Tikhonov regularization ⋮ A GCV based Arnoldi-Tikhonov regularization method ⋮ A majorization-minimization Golub-Kahan bidiagonalization method for \(\ell_2-\ell_q\) mimimization with applications in image restorization ⋮ On the choice of regularization matrix for an \(\ell_2\)-\(\ell_q\) minimization method for image restoration ⋮ Matrix forms of iterative algorithms to solve large-scale discrete ill-posed problems with an application to image restoration

Uses Software

• Regularization tools
• UTV

Cites Work

• Nonlinear total variation based noise removal algorithms
• Arnoldi-Tikhonov regularization methods
• A bidiagonalization algorithm for solving large and sparse ill-posed systems of linear equations
• Regularization methods for large-scale problems
• Tikhonov regularization and the L-curve for large discrete ill-posed problems
• Iterative methods for image deblurring: A Matlab object-oriented approach
• Automatic parameter setting for Arnoldi-Tikhonov methods
• Regularization tools version \(4.0\) for matlab \(7.3\)
• Rank-Deficient and Discrete Ill-Posed Problems
• A Projection‐Based Approach to General‐Form Tikhonov Regularization

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