A frame decomposition of the atmospheric tomography operator

DOI10.1088/1361-6420/aba4fezbMath1448.78011arXiv2002.00880OpenAlexW3041240964MaRDI QIDQ5123685

Simon Hubmer, Ronny Ramlau

Publication date: 29 September 2020

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2002.00880

zbMATH Keywords

singular value decompositionadaptive opticsinverse and ill-posed problemsframe decompositionatmospheric tomography

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Meteorology and atmospheric physics (86A10) Numerical methods for integral transforms (65R10) Radiative transfer in astronomy and astrophysics (85A25) Linear operators and ill-posed problems, regularization (47A52) Inverse problems (including inverse scattering) in optics and electromagnetic theory (78A46) Physical optics (78A10)

Related Items (4)

On regularization via frame decompositions with applications in tomography ⋮ Translation invariant diagonal frame decomposition of inverse problems and their regularization ⋮ Frame decompositions of bounded linear operators in Hilbert spaces with applications in tomography ⋮ Foreword to special issue of Inverse Problems on modern challenges in imaging

Cites Work

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• A gradient-based method for atmospheric tomography
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• The Ill-Conditioned Nature of the Limited Angle Tomography Problem
• An efficient solution to the atmospheric turbulence tomography problem using Kaczmarz iteration
• Inverse problems in astronomical adaptive optics
• Ten Lectures on Wavelets
• A new temporal control approach for SCAO systems
• A Singular-Value-Type Decomposition for the Atmospheric Tomography Operator

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