title: Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation
creator: Lellmann, Jan
creator: Kappes, Jörg
creator: Yuan, Jing
creator: Becker, Florian
creator: Schnörr, Christoph
subject: 510
subject: 510 Mathematics
description: Multi-class labeling is one of the core problems in image analysis. We show how this combinatorial problem can be approximately solved using tools from convex optimization. We suggest a novel functional based on a multidimensional total variation formulation, allowing for a broad range of data terms. Optimization is carried out in the operator splitting framework using Douglas-Rachford Splitting. In this connection, we compare two methods to solve the Rudin-Osher-Fatemi type subproblems and demonstrate the performance of our approach on single- and multichannel images.
date: 2008
type: Preprint
type: info:eu-repo/semantics/preprint
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/8759/1/lellmann08multiclasstv1.pdf
identifier: DOI:10.11588/heidok.00008759
identifier: urn:nbn:de:bsz:16-opus-87593
identifier:   Lellmann, Jan ; Kappes, Jörg ; Yuan, Jing ; Becker, Florian ; Schnörr, Christoph  (2008) Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation.  [Preprint]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/8759/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: ger