Imaging with Kantorovich-Rubinstein discrepancy

 

Authors
Valkonen, Tuomo
Format
Article
Status
publishedVersion
Description

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.
Escuela Polit?cnica Nacional
https://www.scopus.com/record/display.uri?eid=2-s2.0-84919658551&origin=resultslist&sort=plf-f&src=s&st1=

Publication Year
2014
Language
eng
Topic
IMAGING
KANTOROVICH
RUBINSTEIN
DISCREPANCY
Repository
Repositorio SENESCYT
Get full text
http://repositorio.educacionsuperior.gob.ec/handle/28000/2757
Rights
openAccess
License
openAccess