Publications

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Jähne, (2001). Simulation der Austauschprozesse an der Ozeanoberfläche im Labor: das neue Heidelberger Aeolotron. Verhandlungen der Deutschen Physikalischen Gesellschaft, Spring Conference, Hamburg, 26.-30.03.2001. Deutsche Physikalische Gesellschaft
Meister, S, Nair, R and Kondermann, D (2013). Simulation of Time-of-Flight Sensors using Global Illumination. Vision, Modeling and Visualization (VMV), 2013 International Workshop on. Proceedings. 33-40
Küsters, (2004). Simultane Tiefen- und Flussbestimmung pflanzlicher Oberflächen. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/4818
Klar, M, Jehle, M, Detert, M, Jirka, G H, Jähne, B, Köhler, H - J and Wenka, T (2004). Simultaneous 3D PTV and micro-pressure sensor equipment for flow analysis in subsurface gravel layer. Proc. of River Flow 2004. A. A. Balkema Publishers. 703--712
Herzog, A G, Friedl, F and Jähne, B (2010). Simultaneous high-resolution LIF measurements of dissolved gas concentration fields and measurements of wave slope at a wavy free water surface with wind-induced turbulence. 15h Int. Symp on Appl. Laser Techniques to Fluid Mechanics, Lisbon, Portugal, July 05--08, 2010
Jähne, (2014). Simultaneous measurements of solubilities and diffusion coeffcients of volatile species in liquids. 7th SOPRAN Annual Meeting, Bremen, Germany, 25-26 March 2014
Yuan, J, Schnörr, C and Steidl, G (2007). Simultaneous Optical Flow Estimation and Decomposition. SIAM J. Scientific Computing. 29 2283-2304
Yuan, J, Schnörr, C and Steidl, G (2007). Simultaneous Optical Flow Estimation and Decomposition. SIAM J.~Scientific Computing. 29 2283-2304PDF icon Technical Report (1.16 MB)
Wieler, M (2006). Single Tone Frequency Estimation From Very Few Sampling Points. University of Heidelberg
Beyer, M (1997). Skalenraumanalyse nichtlinearer Wasseroberflächenwellen. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Schimpf, U, Haußecker, H, Jähne, B, Jähne, B and Haußecker, H (2000). Small-scale air-sea interaction with thermography. Computer Vision and Applications. A Guide for Students and Practitioners. Academic Press. 638--639
Storath, M, Kiefer, L and Weinmann, A (2019). Smoothing for signals with discontinuities using higher order Mumford-Shah models. Numerische Mathematik. 143(2) 423-460PDF icon Technical Report (1.09 MB)
Jähne, B and Herrmann, H (1997). Softwarekonzepte und Algorithmen für die 3D-Bildverarbeitung. 4. ABW Workshop, TA Esslingen 22.--23.01.1997
Lenzen, F and Berger, J (2015). Solution-Driven Adaptive Total Variation Regularization. LNCS. Springer International Publishing. http://dx.doi.org/10.1007/978-3-319-18461-6_17PDF icon Technical Report (857.29 KB)
Lenzen, F and Berger, J (2015). Solution-Driven Adaptive Total Variation Regularization. LNCS
Pape, C, Beier, T, Li, P, Jain, V, Brock, D D and Kreshuk, A (2017). Solving Large Multicut Problems for Connectomics via Domain Decomposition. Bioimage Computing Workshop. ICCV. 1-10
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J.~Imag.~Sci. 7 2139--2174PDF icon Technical Report (802.13 KB)
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J. Imag. Sci. 7 2139–2174
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving QVIs for Image Restoration with Adaptive Constraint Sets. SIAM Journal on Imaging Sciences (SIIMS), in press
Atif, M, Zimmermann, K and Jähne, B (2010). A space-variant (3D) image simulation tool for computational cameras. International Conference on Computational Photography (ICCP) 2010
Peter, S, Kirschbaum, E, Both, M, Campbell, L A, Harvey, B K, Heins, C, Durstewitz, D, Diego, F and Hamprecht, F A (2017). Sparse convolutional coding for neuronal assembly detection. NIPS, poster
Rother, C (2011). Sparse Higher Order Functions of Discrete Variables–-Representation and Optimization. research.microsoft.com. 45. http://research.microsoft.com/pubs/147370/RotherKohli-SparseHigherOrder.pdf
Diego, F and Hamprecht, F A (2014). Sparse Space-Time Deconvolution for Calcium Image Analysis. NIPS. Proceedings. 64-72. http://papers.nips.cc/paper/5342-sparse-space-time-deconvolution-for-calcium-image-analysisPDF icon Technical Report (5.27 MB)
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166PDF icon Technical Report (866.28 KB)
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166
Petra, S, Schröder, A, Wieneke, B and Schnörr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 294--303PDF icon Technical Report (1014.71 KB)
Petra, S, Schröder, A, Wieneke, B and Schnörr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition – 30th DAGM Symposium. Springer Verlag. 5096 294–303
Wanner, S and Goldlücke, B (2012). Spatial and Angular Variational Superresolution of 4D Light Fields. ECCV 2012. Proceedings, Part 5. Springer. 7576 608-621
Wanner, S and Goldlücke, B (2012). Spatial and Angular Variational Super-Resolution of 4D Light Fields. European Conference on Computer Vision (ECCV)
Jähne, B, Jähne, B and Haußecker, H (1999). Spatial and fourier domain. Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press. 35--66
Wagner, T, Leue, C, Wenig, M, Pfeilsticker, K and Platt, U (2001). Spatial and temporal distribution of enhanced boundary layer BrO concentrations measured by the GOME instrument aboard ERS-2. J. Geophys. Res. 106 24225--24235
Kirchner, M (2004). Spatial Extensions To Self-Modeling Curve Resolution. University of Heidelberg
Klinke, J and Jähne, B (1995). Spatial measurement of short ocean waves during the MBL-ARI West Coast Experiment. IAPSO Proceedings, XXI General Assembly, Honolulu, Hawai, August 1995, PS-10 Spatial Structure of Short Ocean Waves. 390
Rhemann, C, Rother, C, Kohli, P and Gelautz, M (2010). A spatially varying PSF-based prior for alpha matting. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2149–2156
Jehle, M (2006). Spatio-temporal analysis of flows close to water surfaces. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/7060/

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