Structured linear algebra problems in adaptive optics imaging

DOI10.1007/s10444-011-9172-9zbMath1252.78015OpenAlexW2111487535MaRDI QIDQ652573

Sarah Knepper, Johnathan M. Bardsley, James G. Nagy

Publication date: 14 December 2011

Published in: Advances in Computational Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10444-011-9172-9

zbMATH Keywords

preconditioningTikhonov regularizationtruncated singular value decompositionKronecker productgeneralized singular value decompositionimage deblurringLSQRadaptive opticswavefront reconstruction

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Iterative numerical methods for linear systems (65F10) Waves and radiation in optics and electromagnetic theory (78A40) Direct numerical methods for linear systems and matrix inversion (65F05) Geometric optics (78A05) Preconditioners for iterative methods (65F08)

Related Items (9)

An augmented Lagrangian based parallel splitting method for separable convex minimization with applications to image processing ⋮ A note on the alternating direction method of multipliers ⋮ Linearized generalized ADMM-based algorithm for multi-block linearly constrained separable convex programming in real-world applications ⋮ On the convergence rate of the augmented Lagrangian-based parallel splitting method ⋮ Proximal ADMM with larger step size for two-block separable convex programming and its application to the correlation matrices calibrating problems ⋮ A note on augmented Lagrangian-based parallel splitting method ⋮ A partially parallel splitting method for multiple-block separable convex programming with applications to robust PCA ⋮ A distributed Douglas-Rachford splitting method for multi-block convex minimization problems ⋮ A proximal partially parallel splitting method for separable convex programs

Uses Software

• LSQR
• CRAIG

Cites Work

• The ubiquitous Kronecker product
• Wavefront Reconstruction Methods for Adaptive Optics Systems on Ground-Based Telescopes
• LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
• Unnamed Item

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