Lellmann, Jan ; Kappes, Jörg ; Yuan, Jing ; Becker, Florian ; Schnörr, Christoph
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Abstract
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.
| Document type: | Preprint |
|---|---|
| Series Name: | IWR-Preprints |
| Date Deposited: | 06 Nov 2008 14:04 |
| Date: | 2008 |
| Faculties / Institutes: | Service facilities > Interdisciplinary Center for Scientific Computing |
| DDC-classification: | 510 Mathematics |
| Controlled Keywords: | Bildverarbeitung, Konvexe Optimierung, Diskrete Optimierung, Funktion von beschränkter Variation |
