Imaging with Kantorovich--Rubinstein Discrepancy
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Publication:5174331
DOI10.1137/140975528zbMATH Open1308.49043arXiv1407.0221OpenAlexW2079557531MaRDI QIDQ5174331
Author name not available (Why is that?)
Publication date: 17 February 2015
Published in: (Search for Journal in Brave)
Abstract: We propose the use of the Kantorovich-Rubinstein norm from optimal transport in imaging problems. In particular, we discuss a variational regularisation model endowed with a Kantorovich-Rubinstein discrepancy term and total variation regularization in the context of image denoising and cartoon-texture decomposition. We point out connections of this approach to several other recently proposed methods such as total generalized variation and norms capturing oscillating patterns. We also show that the respective optimization problem can be turned into a convex-concave saddle point problem with simple constraints and hence, can be solved by standard tools. Numerical examples exhibit interesting features and favourable performance for denoising and cartoon-texture decomposition.
Full work available at URL: https://arxiv.org/abs/1407.0221
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