Convergence properties of Gauss-Newton iterative algorithms in nonlinear image restoration

DOI10.1007/BF01952237zbMath0734.68100OpenAlexW2020038269WikidataQ113108350 ScholiaQ113108350MaRDI QIDQ811143

Michael Zervakis, Anastasios N. Venetsanopoulos

Publication date: 1991

Published in: Multidimensional Systems and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01952237

zbMATH Keywords

nonlinear optimizationconvergence propertiesimage restorationleast-squares optimizationGauss-Newton algorithmGlobal Convergence Theoremnonlinear iterative algorithms

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10)

Related Items (3)

Limited memory methods with improved symmetric rank-one updates and its applications on nonlinear image restoration ⋮ Design of a new restoration algorithm based on the constrained mean- square-error criterion ⋮ Convergence properties of Gauss-Newton iterative algorithms in nonlinear image restoration

Uses Software

• nlmdl

Cites Work

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• Convergence properties of Gauss-Newton iterative algorithms in nonlinear image restoration
• Design of a new restoration algorithm based on the constrained mean- square-error criterion
• Regularized iterative image restoration with ringing reduction
• Convergence of iterative nonexpansive signal reconstruction algorithms
• Convergence criteria for iterative restoration methods
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Bayesian Methods in Nonlinear Digital Image Restoration
• Improved Methods of Maximum a Posteriori Restoration

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