Convergence of Level Sets in Total Variation Denoising Through Variational Curvatures in Unbounded Domains
Abstract
We present some results of geometric convergence of level sets for solutions of total variation denoising as the regularization parameter tends to zero. The common feature among them is that they make use of explicit constructions of variational mean curvatures for general sets of finite perimeter. Consequently, no additional regularity of the level sets of the ideal data is assumed, and in particular the subgradient of the total variation at it could be empty. In exchange, other restrictions on the data or on the noise are required. We consider two cases: characteristic functions with a parameter choice depending on the noise level, and noiseless generic data.
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Published In
SIAM Journal on Mathematical Analysis
Pages: 1509 - 1545
DOI: 10.1137/20M1346584
ISSN (online): 1095-7154
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© 2021, Society for Industrial and Applied Mathematics.
History
Submitted: 7 July 2020
Accepted: 28 December 2020
Published online: 18 March 2021
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