Image deblurring by sparsity constraint on the Fourier coefficients

DOI10.1007/s11075-015-0047-xzbMath1342.65095OpenAlexW2176514025MaRDI QIDQ297553

Mariarosa Mazza, Marco Donatelli, Debora Sesana, Thomas Kilian Huckle

Publication date: 27 June 2016

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

Full work available at URL: https://doi.org/10.1007/s11075-015-0047-x

zbMATH Keywords

numerical examplefast Fourier transformswaveletdiscrete Fourier transformleast squaresFourier coefficientsTikhonov regularizationimage deblurringfiltering methodsimage deconvolutionsparse reconstruction

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) Numerical methods for wavelets (65T60) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical methods for discrete and fast Fourier transforms (65T50)

Related Items (4)

The finite steps of convergence of the fast thresholding algorithms with \(f\)-feedbacks in compressed sensing ⋮ An \(\ell^2\)-\(\ell^q\) regularization method for large discrete ill-posed problems ⋮ An \(\ell^p\)-\(\ell^q\) minimization method with cross-validation for the restoration of impulse noise contaminated images ⋮ Fast alternating direction multipliers method by generalized Krylov subspaces

Uses Software

• Regularization tools
• RestoreTools

Cites Work

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