Shift-invariant approximations of structured shift-variant blurring matrices

DOI10.1007/s11075-012-9686-3zbMath1263.65021OpenAlexW1978368902MaRDI QIDQ1947184

Claudio Estatico, Fabio Di Benedetto

Publication date: 12 April 2013

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

Full work available at URL: https://doi.org/10.1007/s11075-012-9686-3

zbMATH Keywords

algorithmnumerical resultsinverse problemsimage deblurringcoordinate transformshift-variant imaging systems

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Numerical methods for integral equations (65R20) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Inverse problems for integral equations (45Q05)

Related Items (9)

Structured condition number for a certain class of functions of non-commuting matrices ⋮ Shift-invariant approximations of structured shift-variant blurring matrices ⋮ Computing the Weighted Geometric Mean of Two Large-Scale Matrices and Its Inverse Times a Vector ⋮ Rotational image deblurring with sparse matrices ⋮ On the consistency of the matrix equation \(X^\top A X=B\) when \(B\) is symmetric ⋮ Krylov iterative methods for the geometric mean of two matrices times a vector ⋮ The geometric mean of two matrices from a computational viewpoint ⋮ Sparse Wavelet Representations of Spatially Varying Blurring Operators ⋮ Palindromic linearization and numerical solution of nonsymmetric algebraic \(T\)-Riccati equations

Uses Software

• ImageMagick

Cites Work

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• The circulant operator in the Banach algebra of matrices
• Shift-invariant approximations of structured shift-variant blurring matrices
• Positive definite matrices
• Improved image deblurring with anti-reflective boundary conditions and re-blurring
• Deblurring Images
• Restoring Images Degraded by Spatially Variant Blur
• A Note on Antireflective Boundary Conditions and Fast Deblurring Models
• The geometric mean of two matrices from a computational viewpoint

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