Discrete tomography by continuous multilabeling subject to projection constraints

• Verfasst von: Zisler, Matthias [VerfasserIn]
• Verfasst von: Petra, Stefania [VerfasserIn]
• Verfasst von: Schnörr, Christoph [VerfasserIn]
• Titel: Discrete tomography by continuous multilabeling subject to projection constraints
• Verf.angabe: Matthias Zisler, Stefania Petra, Claudius Schnörr, Christoph Schnörr
• Umfang: 12 S.
• Fussnoten: Gesehen am 13.03.2018
• Titel Quelle: Enthalten in: Pattern Recognition
• Jahr Quelle: 2016
• Band/Heft Quelle: (2016), S. 261-272
• ISBN Quelle: 978-3-319-45886-1
• DOI: doi:10.1007/978-3-319-45886-1_21
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1571004955

Abstract

We present a non-convex variational approach to non-binary discrete tomography which combines non-local projection constraints with a continuous convex relaxation of the multilabeling problem. Minimizing this non-convex energy is achieved by a fixed point iteration which amounts to solving a sequence of convex problems, with guaranteed convergence to a critical point. A competitive numerical evaluation using standard test-datasets demonstrates a significantly improved reconstruction quality for noisy measurements from a small number of projections.