A non-iterative regularization approach to blind deconvolution

DOI10.1088/0266-5611/22/3/003zbMath1112.65130OpenAlexW1991596255MaRDI QIDQ5478585

L. Justen, Ronny Ramlau

Publication date: 13 July 2006

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

Full work available at URL: https://doi.org/10.1088/0266-5611/22/3/003

zbMATH Keywords

convergenceimage processingnonlinear ill-posed problemTikhonov regularizationblind deconvolutionminimum norm solutionsnonlinear inversion operator

Mathematics Subject Classification ID

Numerical methods for integral equations (65R20) Other nonlinear integral equations (45G10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical methods for ill-posed problems for integral equations (65R30)

Related Items (8)

Bayesian inverse problems with unknown operators ⋮ Extensions of the Justen-Ramlau blind deconvolution method ⋮ Lanczos-based fast blind deconvolution methods ⋮ Joint super-resolution image reconstruction and parameter identification in imaging operator: analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging ⋮ Non-convex regularization of bilinear and quadratic inverse problems by tensorial lifting ⋮ A general framework for soft-shrinkage with applications to blind deconvolution and wavelet denoising ⋮ Tensor-free proximal methods for lifted bilinear/quadratic inverse problems with applications to phase retrieval ⋮ Bilevel optimization for calibrating point spread functions in blind deconvolution

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