A Semiblind Regularization Algorithm for Inverse Problems with Application to Image Deblurring

DOI10.1137/16M1101830zbMath1383.65058MaRDI QIDQ4603506

Ronny Ramlau, Marco Donatelli, Alessandro Buccini

Publication date: 21 February 2018

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

zbMATH Keywords

algorithmconvergencenumerical exampleinverse problemnonconvex optimizationimage deblurringnoisy operatorregularization of ill-posed problemssemiblind deconvolution

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Nonlinear ill-posed problems (47J06) Numerical solutions to equations with nonlinear operators (65J15) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Numerical solution to inverse problems in abstract spaces (65J22)

Related Items (9)

Operator Shifting for General Noisy Matrix Systems ⋮ Edge adaptive hybrid regularization model for image deblurring ⋮ Limited memory restarted \(\ell^p\)-\(\ell^q\) minimization methods using generalized Krylov subspaces ⋮ Bilevel inverse problems in neuromorphic imaging ⋮ Operator shifting for noisy elliptic systems ⋮ Lanczos-based fast blind deconvolution methods ⋮ Fast alternating direction multipliers method by generalized Krylov subspaces ⋮ Solving inverse problems using data-driven models ⋮ Applying smoothing technique and semi-proximal ADMM for image deblurring

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