Structural Properties of Solutions to Total Variation Regularization Problems
Open Access
- 1 July 2000
- journal article
- research article
- Published by EDP Sciences in ESAIM: Mathematical Modelling and Numerical Analysis
- Vol. 34 (4) , 799-810
- https://doi.org/10.1051/m2an:2000104
Abstract
In dimension one it is proved that the solution to a total variation-regularized least-squares problem is always a function which is "constant almost everywhere" , provided that the data are in a certain sense outside the range of the operator to be inverted. A similar, but weaker result is derived in dimension two.Keywords
This publication has 15 references indexed in Scilit:
- BV-type regularization methods for convoluted objects with edge, flat and grey scalesInverse Problems, 2000
- An active set strategy based on the augmented Lagrangian formulation for image restorationESAIM: Mathematical Modelling and Numerical Analysis, 1999
- Image recovery via total variation minimization and related problemsNumerische Mathematik, 1997
- Regularization of linear least squares problems by total bounded variationESAIM: Control, Optimisation and Calculus of Variations, 1997
- Analysis of regularized total variation penalty methods for denoisingInverse Problems, 1996
- Recovery of Blocky Images from Noisy and Blurred DataSIAM Journal on Applied Mathematics, 1996
- Analysis of bounded variation penalty methods for ill-posed problemsInverse Problems, 1994
- PrefacePublished by Elsevier ,1993
- Functions of Bounded Variation and Caccioppoli SetsPublished by Springer Nature ,1984
- Elliptic Partial Differential Equations of Second OrderPublished by Springer Nature ,1977