{"intvolume":" 10302","month":"06","doi":"10.1007/978-3-319-58771-4_19","publist_id":"7132","date_created":"2018-12-11T11:47:41Z","date_published":"2017-06-01T00:00:00Z","ec_funded":1,"_id":"646","publisher":"Springer","scopus_import":1,"quality_controlled":"1","date_updated":"2021-01-12T08:07:34Z","oa_version":"Submitted Version","day":"01","type":"conference","year":"2017","alternative_title":["LNCS"],"publication_identifier":{"isbn":["978-331958770-7"]},"page":"235 - 246","title":"A novel convex relaxation for non binary discrete tomography","department":[{"_id":"VlKo"}],"language":[{"iso":"eng"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Jan","last_name":"Kuske","full_name":"Kuske, Jan"},{"first_name":"Paul","id":"446560C6-F248-11E8-B48F-1D18A9856A87","full_name":"Swoboda, Paul","last_name":"Swoboda"},{"full_name":"Petra, Stefanie","last_name":"Petra","first_name":"Stefanie"}],"citation":{"ama":"Kuske J, Swoboda P, Petra S. A novel convex relaxation for non binary discrete tomography. In: Lauze F, Dong Y, Bjorholm Dahl A, eds. Vol 10302. Springer; 2017:235-246. doi:10.1007/978-3-319-58771-4_19","apa":"Kuske, J., Swoboda, P., & Petra, S. (2017). A novel convex relaxation for non binary discrete tomography. In F. Lauze, Y. Dong, & A. Bjorholm Dahl (Eds.) (Vol. 10302, pp. 235–246). Presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark: Springer. https://doi.org/10.1007/978-3-319-58771-4_19","chicago":"Kuske, Jan, Paul Swoboda, and Stefanie Petra. “A Novel Convex Relaxation for Non Binary Discrete Tomography.” edited by François Lauze, Yiqiu Dong, and Anders Bjorholm Dahl, 10302:235–46. Springer, 2017. https://doi.org/10.1007/978-3-319-58771-4_19.","ista":"Kuske J, Swoboda P, Petra S. 2017. A novel convex relaxation for non binary discrete tomography. SSVM: Scale Space and Variational Methods in Computer Vision, LNCS, vol. 10302, 235–246.","ieee":"J. Kuske, P. Swoboda, and S. Petra, “A novel convex relaxation for non binary discrete tomography,” presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark, 2017, vol. 10302, pp. 235–246.","short":"J. Kuske, P. Swoboda, S. Petra, in:, F. Lauze, Y. Dong, A. Bjorholm Dahl (Eds.), Springer, 2017, pp. 235–246.","mla":"Kuske, Jan, et al. A Novel Convex Relaxation for Non Binary Discrete Tomography. Edited by François Lauze et al., vol. 10302, Springer, 2017, pp. 235–46, doi:10.1007/978-3-319-58771-4_19."},"abstract":[{"text":"We present a novel convex relaxation and a corresponding inference algorithm for the non-binary discrete tomography problem, that is, reconstructing discrete-valued images from few linear measurements. In contrast to state of the art approaches that split the problem into a continuous reconstruction problem for the linear measurement constraints and a discrete labeling problem to enforce discrete-valued reconstructions, we propose a joint formulation that addresses both problems simultaneously, resulting in a tighter convex relaxation. For this purpose a constrained graphical model is set up and evaluated using a novel relaxation optimized by dual decomposition. We evaluate our approach experimentally and show superior solutions both mathematically (tighter relaxation) and experimentally in comparison to previously proposed relaxations.","lang":"eng"}],"volume":10302,"conference":{"end_date":"2017-06-08","start_date":"2017-06-04","name":"SSVM: Scale Space and Variational Methods in Computer Vision","location":"Kolding, Denmark"},"project":[{"name":"Discrete Optimization in Computer Vision: Theory and Practice","_id":"25FBA906-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"616160"}],"status":"public","publication_status":"published","editor":[{"first_name":"François","full_name":"Lauze, François","last_name":"Lauze"},{"full_name":"Dong, Yiqiu","last_name":"Dong","first_name":"Yiqiu"},{"first_name":"Anders","full_name":"Bjorholm Dahl, Anders","last_name":"Bjorholm Dahl"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1703.03769"}],"oa":1}