Publikationen der AG Inverse Probleme und Bildverarbeitung

Zeitschriftenartikel (7)

1. D. Lorenz, A. Tillmann, M. E. Pfetsch.
   An infeasible-point subgradient method using adaptive approximate projections.
   Computational Optimization and Applications, 57(2):271-306, 2014.

   DOI: 10.1007/s10589-013-9602-3
   online unter: http://arxiv.org/abs/1104.5351

2. D. Lorenz, B. Komander, M. Fischer, M. Petz, R. Tutsch.
   Data fusion of surface normals and point coordinates for deflectometric measurements.
   Journal of Sensors and Sensor Systems, 3:281-290, 2014.

   DOI: 10.5194/jsss-3-281-2014

3. D. Lorenz, J. Lellmann, C. Schönlieb, T. Valkonen.
   Imaging with Kantorovich-Rubinstein discrepancy.
   SIAM Journal on Imaging Sciences, 7(4):2833-2859, 2014.

   DOI: 10.1137/140975528
   online unter: http://arxiv.org/abs/1407.0221

4. D. Lorenz, M. Matz, K. Schumacher, K. Hatlapatka, K. Baumann.
   Observer-independent quantification of insulin granule exocytosis and pre-exocytotic mobility by TIRF microscopy.
   Microscopy and Microanalysis, 20(1):206-218, 2014.

   DOI: 10.1017/S1431927613013767

5. E. Herrholz, D. Lorenz, G. Teschke, D. Trede.
   Sparsity and Compressed Sensing in Inverse Problems.
   Lecture Notes in Computational Science and Engineering, 102:365-379, Springer Verlag, 2014.

   DOI: 10.1007/978-3-319-08159-5_18

6. D. Lorenz, C. Kruschel, J. S. Jørgensen.
   Testable uniqueness conditions for empirical assessment of undersampling levels in total variation-regularized x-ray CT.
   Inverse Problems in Science and Engineering, 23:1283-1305, 2014.

   DOI: 10.1080/17415977.2014.986724
   online unter: http://arxiv.org/abs/1409.0214

7. D. Lorenz, S. Wenger, F. Schöpfer.
   The linearized Bregman method via split feasibility problems: Analysis and generalizations.
   SIAM Journal on Imaging Sciences, 2(7), 2014.

   DOI: 10.1137/130936269
   online unter: http://arxiv.org/abs/1309.2094

Tagungsbeiträge (1)

1. D. Lorenz, F. Schöpfer, S. Wenger, M. Magnor.
   sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing.
   IEEE International Conference on Image Processing.
   

   Recognized as one of the “Top 10%” papers

   DOI: 10.1109/ICIP.2014.7025269
   online unter: http://arxiv.org/abs/1403.7543