Constrained numerical optimization methods for blind deconvolution

DOI10.1007/s11075-013-9693-zzbMath1281.65066OpenAlexW2018496583MaRDI QIDQ393752

Elena Loli Piccolomini, James G. Nagy, Anastasia Cornelio

Publication date: 24 January 2014

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

Full work available at URL: https://doi.org/10.1007/s11075-013-9693-z

zbMATH Keywords

algorithmnumerical experimentsTikhonov regularizationGauss-Newton methodnonlinear least squaresblind deconvolutionimplicit filteringnonlinear ill-posed inverse problemvariable projection

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Ill-posedness and regularization problems in numerical linear algebra (65F22)

Related Items

Numerical approximation of partial differential equations by a variable projection method with artificial neural networks, Parametric PSF estimation based on recursive SURE for sparse deconvolution, The Sylvester Resultant Matrix and Image Deblurring, Variable projection methods for separable nonlinear inverse problems with general-form Tikhonov regularization, Lanczos-based fast blind deconvolution methods, Secant variable projection method for solving nonnegative separable least squares problems, Nonlinear least-squares spline fitting with variable knots, Motion Estimation and Correction in Photoacoustic Tomographic Reconstruction

Uses Software

• IMFIL
• KELLEY
• SPARX

Cites Work

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