Convergence of variational regularization methods for imaging on Riemannian manifolds

DOI10.1088/0266-5611/28/1/015007zbMath1234.65023arXiv1105.2407OpenAlexW3103992540WikidataQ115293869 ScholiaQ115293869MaRDI QIDQ3224126

Nicolas Thorstensen, Otmar Scherzer

Publication date: 29 March 2012

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

Full work available at URL: https://arxiv.org/abs/1105.2407

zbMATH Keywords

stabilityconvergencecomputer visionnumerical experimentsHilbert spacescompact linear operatorabstract operator equationsfinite-dimensional Riemannian manifoldslinear inverse ill-posed problemTikhonov-type regularization methods

Mathematics Subject Classification ID

Numerical solutions to equations with linear operators (65J10) Applications of variational problems in infinite-dimensional spaces to the sciences (58E50) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Linear operators and ill-posed problems, regularization (47A52) Numerical solution to inverse problems in abstract spaces (65J22) Computational issues in computer and robotic vision (65D19)

Related Items (1)

Reconstructing a function on the sphere from its means along vertical slices

This page was built for publication: Convergence of variational regularization methods for imaging on Riemannian manifolds