Publications of the MIA Group

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  1. T. Schneevoigt, C. Schroers, J. Weickert:
    A dense pipeline for 3D reconstruction from image sequences.
    In X. Jiang, J. Hornegger, R. Koch (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Springer, Berlin, 2014, in press.
  2. N. Persch, C. Schroers, S. Setzer, J. Weickert:
    Introducing more physics into variational depth-from-defocus.
    In X. Jiang, J. Hornegger, R. Koch (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Springer, Berlin, 2014, in press.
  3. O. Demetz, M. Stoll, S. Volz, J. Weickert, A. Bruhn:
    Learning brightness transfer functions for the joint recovery of illumination changes and optical flow.
    Proc. 13th European Conference on Computer Vision (ECCV 2014, Zurich, Switzerland, Sept. 2014), in press.
  4. C. Schroers, S. Setzer, J. Weickert:
    A variational taxonomy for surface reconstruction from oriented points.
    Computer Graphics Forum (Proc. 2014 Eurographics Symposium on Geometry Processing), in press.
  5. D. Hafner, O. Demetz, J. Weickert, M. Reißel:
    Mathematical foundations and generalisations of the census transform for robust optic flow computation.
    Journal of Mathematical Imaging and Vision, in press.
    Revised version of Technical Report No. 337,
    Department of Mathematics, Saarland University, Saarbrücken, Germany, Oct. 2013.
  6. P. Peter, J. Weickert:
    Colour image compression with anisotropic diffusion.
    Proc. 21st IEEE International Conference on Image Processing (ICIP 2014, Paris, France, October 2014), in press.
  7. D. Hafner, O. Demetz, J. Weickert:
    Simultaneous HDR and optic flow computation.
    Proc. 22nd International Conference on Pattern Recognition (ICPR 2014, Stockholm, Sweden, August 2014), IEEE Computer Society Press, 2014, in press.
  8. M. Krause, R. M. Alles, B. Burgeth, J. Weickert:
    Fast retinal vessel analysis.
    Journal of Real-Time Image Processing, Online First.
    Also available as Technical Report No. 320, Department of Mathematics, Saarland University, Saarbrücken, Germany, Dec. 2012 (revised Febr. 2013).
  9. C. Schmaltz, P. Peter, M. Mainberger, F. Ebel, J. Weickert, A. Bruhn:
    Understanding, optimising, and extending data compression with anisotropic diffusion.
    International Journal of Computer Vision, Vol. 108, No. 3, 222-240, July 2014.
    Revised version of Technical Report No. 329, Department of Mathematics, Saarland University, Saarbrücken, Germany, March 2013.
  10. P. Gwosdek, C. Schmaltz, J. Weickert, T. Teuber:
    Fast electrostatic halftoning.
    Journal of Real-Time Image Processing, Vol. 9, No. 2, 379-392, June 2014.
    Revised version of Technical Report No. 295, Department of Mathematics, Saarland University, Saarbrücken, Germany, June 2011.
  11. O. Demetz, D. Hafner, J. Weickert:
    Morphologically Invariant Matching of Structures with the Complete Rank Transform.
    Technical Report No. 348, Department of Mathematics, Saarland University, Saarbrücken, Germany, May 2014.
  12. S. F. Huckemann, K.-R. Kim, A. Munk, F. Rehfeld, M. Sommerfeld, J. Weickert, C. Wollnik:
    The circular SiZer, inferred persistence of shape parameters and application to stem cell stress fibre structures.
    arXiv:1404.3300 [stat.ME], April 2014.
  13. M. Boshtayeva, D. Hafner, J. Weickert:
    A Focus Fusion Framework with Anisotropic Depth Map Smoothing.
    Technical Report No. 343, Department of Mathematics, Saarland University, Saarbrücken, Germany, February 2014.
  14. C. Schmaltz, N. Mach, M. Mainberger, J. Weickert:
    Progressive modes in PDE-based image compression.
    Proc. 30th Picture Coding Symposium (PCS 2013, San Jose, CA, Dec. 2013, San Jose, CA). IEEE, Piscataway, 2013.

  15. M. Hein, S. Setzer, L. Jost, S. Rangapuram:
    The total variation on hypergraphs - Learning on hypergraphs revisited.
    In C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger (Eds.): Advances in Neural Information Processing, (Proc. NIPS 2013, Lake Tahoe, NE, Dec. 2013). Vol. 26, 2013.

  16. S. Gehrig, M. Reznitskii, N. Schneider, U. Franke, J. Weickert:
    Priors for stereo vision under adverse weather conditions.
    In Proc. First International Workshop on Computer Vision for Autonomous Driving (CVAD 2013, Sydney, Australia, Dec. 2013). IEEE, Piscataway, 2013.

  17. N. Persch, A. Elhayek, M. Welk, A. Bruhn, S. Grewenig, K. Böse, A. Kraegeloh, J. Weickert:
    Enhancing 3-D cell structures in confocal and STED microscopy: A joint model for interpolation, deblurring and anisotropic smoothing.
    Measurement Science and Technology, Vol. 24, No. 12, 125703, Dec. 2013.
    Revised version of Technical Report No. 321, Department of Mathematics, Saarland University, Saarbrücken, Germany, Jan. 2013.
  18. S. Hoffmann, J. D. Shutler, M. Lobbes, B. Burgeth, A. Meyer-Bäse:
    Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique.
    EURASIP Journal on Advances in Signal Processing, Vol. 2013, Paper 172, Nov. 2013.

  19. O. Demetz, D. Hafner, J. Weickert:
    The complete rank transform: A tool for accurate and morphologically invariant matching of structures.
    In T. Burghardt, D. Damen, W. Mayol-Cuevas, M. Mirmehdi (Eds.): Proc. 24th British Machine Vision Conference, BMVA Press, 2013.
    Awarded the Maria Petrou Prize for Invariance in Computer Vision.
  20. A. Hewer, J. Weickert, T. Scheffer, H. Seibert, S. Diebels:
    Lagrangian strain tensor computation with higher order variational models.
    In T. Burghardt, D. Damen, W. Mayol-Cuevas, M. Mirmehdi (Eds.): Proc. 24th British Machine Vision Conference, BMVA Press, 2013.
  21. J. Weickert, M. Hein, B. Schiele (Eds.):
    Pattern Recognition.
    Lecture Notes in Computer Science, Vol. 8142, Springer, Berlin, 2013.
  22. J. Weickert, K. Hagenburg, M. Breuß, O. Vogel:
    Linear osmosis models for visual computing.
    In A. Heyden, F. Kahl, C. Olsson, M. Oskarsson, X.-C. Tai (Eds.): Energy Minimization Methods in Computer Vision and Pattern Recognition. Lecture Notes in Computer Science, Vol. 8081, 26-39, Springer, Berlin, 2013.
  23. L. Hoeltgen, S. Setzer, J. Weickert:
    An optimal control approach to find sparse data for Laplace interpolation.
    In A. Heyden, F. Kahl, C. Olsson, M. Oskarsson, X.-C. Tai (Eds.): Energy Minimization Methods in Computer Vision and Pattern Recognition. Lecture Notes in Computer Science, Vol. 8081, 151-164, Springer, Berlin, 2013.
  24. M. Boshtayeva, D. Hafner, J. Weickert:
    Focus fusion with anisotropic depth map smoothing.
    In A. Bors, E. Hancock, W. Smith, R. Wilson (Eds.): Computer Analysis of Images and Patterns. Lecture Notes in Computer Science, Vol. 8048, 67-74, Springer, Berlin, 2013.
  25. D. Hafner, O. Demetz, J. Weickert:
    Why is the census transform good for robust optic flow computation?
    In A. Kuijper, K. Bredies, T. Pock, H. Bischof (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 7893, 210-221, Springer, Berlin, 2013.
  26. S. Hoffmann, M. Mainberger, J. Weickert, M. Puhl:
    Compression of depth maps with segment-based homogeneous diffusion.
    In A. Kuijper, K. Bredies, T. Pock, H. Bischof (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 7893, 319-330, Springer, Berlin, 2013.
  27. O. Vogel, K. Hagenburg, J. Weickert, S. Setzer:
    A fully discrete theory for linear osmosis filtering.
    In A. Kuijper, K. Bredies, T. Pock, H. Bischof (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 7893, 368-379, Springer, Berlin, 2013.
  28. J. Weickert, M. Welk, M. Wickert:
    L2-stable nonstandard finite differences for anisotropic diffusion.
    In A. Kuijper, K. Bredies, T. Pock, H. Bischof (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 7893, 380-391, Springer, Berlin, 2013.

  29. M. Breuß, D. Dietrich:
    On the optimization of flux limiter schemes for hyperbolic conservation laws.
    Numerical Methods for Partial Differential Equations, Vol. 29, No. 3, 884-896, May 2013.
    Revised version of
    M. Breuß, D. Dietrich: Fuzzy flux limiter schemes for hyperbolic conservation laws.
    Technical Report No. 258, Department of Mathematics, Saarland University, Saarbrücken, Germany, February 2010.
  30. S. Setzer, G. Steidl, J. Morgenthaler:
    A cyclic projected gradient method.
    Computational Optimization and Applications, Vol. 54, No. 2, 417-440, March 2013.
  31. P. Peter and M. Breuß:
    Refined homotopic thinning algorithms and quality measures for skeletonisation methods.
    In M. Breuß, A. Bruckstein, P. Maragos (Eds.): Innovations for Shape Analysis: Models and Algorithms. Pages 77-92, Springer, Berlin, 2013.
    Revised version of Technical Report No. 312, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2012.
  32. T. Bühler, S. Rangapuram, M. Hein, S. Setzer:
    Constrained fractional set programs and their application in local clustering and community detection.
    Journal of Machine Learning Research, Vol. 28, No. 1, 624-632, 2013.
  33. S. Grewenig, J. Weickert, C. Schroers, A. Bruhn:
    Cyclic Schemes for PDE-Based Image Analysis.
    Technical Report No. 327, Department of Mathematics, Saarland University, Saarbrücken, Germany, March 2013.
  34. V. Kramarev, O. Demetz, C. Schroers, J. Weickert:
    Cross anisotropic cost volume filtering for segmentation.
    In K. M. Lee, Y. Matsushita, J. M. Rehg, Z. Hu (Eds.): Computer Vision - ACCV 2012. Lecture Notes in Computer Science Vol. 7724, 803-814. Springer, Berlin, 2013.
  35. P. Gwosdek, H. Zimmer, S. Grewenig, A. Bruhn, J. Weickert:
    A highly efficient GPU implementation for variational optic flow based on the Euler-Lagrange framework.
    In K. N. Kutulakos (Ed.): Trends and Topics in Computer Vision.
    Lecture Notes in Computer Science, Vol. 6554, 372-383, Springer, Berlin, 2012.
    Revised version of Technical Report No. 267, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2010.
    See also: Supplementary Material Webpage.
  36. D. Kondermann, S. Abraham, G. Brostow, W. Förstner, S. Gehrig, A. Imiya, B. Jähne, F. Klose, M. Magnor, H. Mayer, R. Mester, T. Pajdla, R. Reulke, H. Zimmer:
    On performance analysis of optical flow algorithms.
    In F. Dellaert, J.-M. Frahm, M. Pollefeys, B. Rosenhahn, L. Leal-Taixe (Eds.): Outdoor and Large-Scale Real-World Scene Analysis. Pages 329-355, Lecture Notes in Computer Science, Vol. 7474, Springer, Berlin, 2012.
  37. C. Schmaltz, P. Gwosdek, J. Weickert:
    Multi-class anisotropic electrostatic halftoning.
    Computer Graphics Forum, Vol. 31, No. 6, 1924-1935, September 2012.
    Revised version of Technical Report No. 301, Department of Mathematics, Saarland University, Saarbrücken, Germany, Oct. 2011.
    See also: Supplementary Material Webpage.
  38. R. Moreno, L. Pizarro, B. Burgeth, J. Weickert, M. A. Garcia, D. Puig:
    Adaptation of tensor voting to image structure estimation.
    In D. H. Laidlaw, A. Vilanova (Eds.): New Developments in the Visualization and Processing of Tensor Fields. Pages 29-50, Springer, Berlin, 2012.
    Also available as Linköping University Postprint.

  39. Y. C. Ju, M. Breuß, A. Bruhn, S. Galliani:
    Shape from shading for rough surfaces: Analysis of the Oren-Nayar model.
    In Proc. 23rd British Machine Vision Conference (Sept. 3-7, Surrey, UK). Pages 104.1-104.11, BMVA Press, 2012.
  40. S. Galliani, M. Breuß, Y. C. Ju:
    Fast and robust surface normal integration by a discrete eikonal equation.
    In Proc. 23rd British Machine Vision Conference (Sept. 3-7, Surrey, UK). Pages 106.1-106.11, BMVA Press, 2012.
  41. C. Schroers, H. Zimmer, L. Valgaerts, A. Bruhn, O. Demetz, J. Weickert:
    Anisotropic range image integration.
    In A. Pinz, T. Pock, H. Bischof, F. Leberl (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 7476, 73-82, Springer, Berlin, 2012.
    Awarded a DAGM-OAGM 2012 Paper Prize.
  42. C. Schmaltz, J. Weickert:
    Video compression with 3-D pose tracking, PDE-based image coding, and electrostatic halftoning.
    In A. Pinz, T. Pock, H. Bischof, F. Leberl (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 7476, 438-447, Springer, Berlin, 2012.
  43. P. Peter:
    Three-dimensional data compression with anisotropic diffusion.
    In Proc. DAGM-OAGM 2012 Symposium for Pattern Recognition, Young Researchers Forum. Graz, Austria, August 28-31, 2012.
  44. L. Lau Rakêt, L. Roholm, A. Bruhn, J. Weickert:
    Motion compensated frame interpolation with a symmetrical optical flow constraint.
    In G. Bebis, R. Boyle, B. Parvin, D. Koracin, C. Fowlkes, S. Wang, M.-H. Choi, S. Mantler, J. Schulze, D. Acevedo, K. Mueller, M. Papka (Eds.): Advances in Visual Computing, Part I. Lecture Notes in Computer Science, Vol. 7431, 447-457, Springer, Berlin, 2012.

  45. M. Mainberger, C. Schmaltz, M. Berg, J. Weickert, M. Backes:
    Diffusion-based image compression in steganography.
    In G. Bebis, R. Boyle, B. Parvin, D. Koracin, C. Fowlkes, S. Wang, M.-H. Choi, S. Mantler, J. Schulze, D. Acevedo, K. Mueller, M. Papka (Eds.): Advances in Visual Computing, Part II. Lecture Notes in Computer Science, Vol. 7432, 219-228, Springer, Berlin, 2012.

  46. S. Hoffmann, J. Shutler, M. Lobbes, B. Burgeth, A. Meyer-Bäse:
    Automated analysis of single and joint kinetic and morphologic features for non-masses.
    In H. Szu (Ed.): Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X. Proc. SPIE, Vol. 8401, 2012.

  47. J. Weickert:
    Mathematische Bildverarbeitung mit Ideen aus der Natur.
    Mitteilungen der DMV, Heft 20, 82-90, 2012.
    Also available as Technical Report No. 310, Department of Mathematics, Saarland University, Saarbrücken, Germany, June 2012.
  48. T. Goldstein, B. O'Donoghue, S. Setzer, R. Baraniuk:
    Fast Alternating Direction Optimization Methods.
    Technical Report CAM 12-35, Department of Mathematics, University of California at Los Angeles, CA, May 2012 (updated Sept. 2012).
  49. C. Schmaltz, B. Rosenhahn, T. Brox, J. Weickert:
    Region based pose tracking with occlusions using 3D models.
    Machine Vision and Applications, Vol. 23, No. 3, 557-577, May 2012.
    Revised version of Technical Report No. 277, Department of Mathematics, Saarland University, Saarbrücken, Germany, October 2010.
  50. M. Breuß, E. Cristiani, J.-D. Durou, M. Falcone, O. Vogel:
    Perspective shape from shading: Ambiguity analysis and numerical approximations.
    SIAM Journal on Imaging Sciences, Vol. 5, No. 1, 311-342, March 2012.
    Revised version of Technical Report No. 281, Department of Mathematics, Saarland University, Saarbrücken, Germany, Nov. 2010.
  51. S. Setzer, G. Steidl, T. Teuber:
    On vector and matrix median computation.
    Journal of Computational and Applied Mathematics, Vol. 236, No. 8, 2200-2222, February 2012.
  52. B. Burgeth, L. Pizarro, S. Didas, J. Weickert:
    3D coherence-enhancing diffusion filtering for matrix fields.
    In L. Florack, R. Duits, G. Jongbloed, M.-C. van Lieshout, L. Davies (Eds.): Mathematical Methods for Signal and Image Analysis and Representation. Pages 49-63, Springer, Berlin, 2012.
  53. L. Valgaerts, A. Bruhn, M. Mainberger, J. Weickert:
    Dense versus sparse approaches for estimating the fundamental matrix.
    International Journal of Computer Vision, Vol. 96, No. 2, 212-234, Jan. 2012.
    Revised version of Technical Report No. 263, Department of Mathematics, Saarland University, Saarbrücken, Germany, October 2010.
  54. M. Mainberger, S. Hoffmann, J. Weickert, C. H. Tang, D. Johannsen, F. Neumann, B. Doerr:
    Optimising spatial and tonal data for homogeneous diffusion inpainting.
    In A. M. Bruckstein, B. ter Haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 6667, 26-37, Springer, Berlin, 2012.
  55. P. Gwosdek, S. Grewenig, A. Bruhn, J. Weickert:
    Theoretical foundations of Gaussian convolution by extended box filtering.
    In A. M. Bruckstein, B. ter Haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 6667, 447-458, Springer, Berlin, 2012.
  56. K. Hagenburg, M. Breuß, J. Weickert, O. Vogel:
    Novel schemes for hyperbolic PDEs using osmosis filters from visual computing.
    In A. M. Bruckstein, B. ter Haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 6667, 532-543, Springer, Berlin, 2012.
  57. A. Luxenburger, H. Zimmer, P. Gwosdek, J. Weickert:
    Fast PDE-based image analysis in your pocket.
    In A. M. Bruckstein, B. ter Haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 6667, 544-555, Springer, Berlin, 2012.
  58. O. Demetz, J. Weickert, A. Bruhn, H. Zimmer:
    Optic flow scale space.
    In A. M. Bruckstein, B. ter Haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 6667, 713-724, Springer, Berlin, 2012.
  59. M. Hein, S. Setzer:
    Beyond spectral clustering: Relaxations of balanced graph cuts.
    Advances in Neural Information Processing Systems (Proc. NIPS, Dec. 2011, Granada, Spain), Vol. 24, 2011.
  60. S. Volz, A. Bruhn, L. Valgaerts, H. Zimmer:
    Modeling temporal coherence for optical flow.
    In Proc. 13th IEEE International Conference on Computer Vision (ICCV 2011, Barcelona, Spain, Nov. 6-13), 2011.
  61. R. Moreno, M. A. Garcia, D. Puig, L. Pizarro, B. Burgeth, J. Weickert:
    On improving the efficiency of tensor voting.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 1, 2215-2228, Nov. 2011.
    Also available as Linköping University Postprint.
  62. M. Breuß, Y. C. Ju:
    Shape from shading with specular highlights: analysis of the Phong model.
    Proc. 18th IEEE International Conference on Image Processing (ICIP 2011, Brussels, Belgium, September 11-14, 2011), 9-12, 2011.
  63. S. Setzer, G. Steidl, T. Teuber:
    Infimal convolution regularizations with discrete l1-type functionals.
    Communications in Mathematical Sciences, Vol. 9, No. 3, 797-827, Nov. 2011.
  64. M. Breuß, E. Cristiani, P. Gwosdek, O. Vogel:
    A domain-decomposition-free parallelisation of the fast marching method.
    Applied Mathematics and Computation, Vol. 218, No. 1, 32-44, Sept. 2011.
    Revised version of Technical Report No. 250, Department of Mathematics, Saarland University, Saarbrücken, Germany, October 2009.
  65. G. Peyre, L. D. Cohen, J. Weickert (Eds.):
    Mathematics and Image Analysis.
    Special Issue of Journal of Mathematical Imaging and Vision, Vol. 41, No. 1-2, Sept. 2011.

  66. A. Elhayek, M. Welk, J. Weickert:
    Simultaneous interpolation and deconvolution model for the 3-D reconstruction of cell images.
    In M. Felsberg, R. Mester (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 6835, 316-325, Springer, Berlin, 2011.
  67. L. Hoeltgen, S. Setzer, M. Breuß:
    Intermediate flow field filtering in energy based optic flow computations.
    In Y. Boykov, V. Lempitsky, F. R. Schmidt (Eds.): Energy Minimazation Methods in Computer Vision and Pattern Recognition. Lecture Notes in Computer Science, Vol. 6819, 315-328, Springer, Berlin, 2011.
  68. M. Mainberger, A. Bruhn, J. Weickert, S. Forchhammer:
    Edge-based compression of cartoon-like images with homogeneous diffusion.
    Pattern Recognition, Vol. 44, No. 9, 1859-1873, September 2011.
    Also available as Technical Report No. 269, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2010.
  69. H. Zimmer, A. Bruhn, J. Weickert:
    Optic flow in harmony.
    International Journal of Computer Vision, Vol. 93, No. 3, 368-388, July 2011.
    Revised version of Technical Report No. 272, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2010.
  70. S. Setzer:
    Operator splittings, Bregman methods and frame shrinkage in image processing.
    International Journal of Computer Vision, Vol. 92, No. 3, 265-280, May 2011.
  71. A. Heyden, K. Mørken, X. Tai, J. Weickert (Eds.):
    Scale Space and Variational Methods in Computer Vision.
    Special Issue of International Journal of Computer Vision, Vol. 92, No. 3, May 2011.
  72. A. Heyden, K. Mørken, X. Tai, J. Weickert (Eds.):
    Scale Space and Variational Methods in Computer Vision.
    Special Issue of International Journal of Computer Vision, Vol. 92, No. 2, April 2011.
  73. M. Breuß, J. Weickert:
    Highly accurate schemes for PDE-based morphology with general structuring elements.
    International Journal of Computer Vision, Vol. 92, No. 2, 132-145, April 2011.
    Revised version of Technical Report No. 236, Department of Mathematics, Saarland University, Saarbrücken, Germany, May 2009.
  74. B. Burgeth, L. Pizarro, M. Breuß, J. Weickert:
    Adaptive continuous-scale morphology for matrix fields.
    International Journal of Computer Vision, Vol. 92, No. 2, 146-161, April 2011.
    Revised version of Technical Report No. 237, Department of Mathematics, Saarland University, Saarbrücken, Germany, May 2009.
  75. H. Zimmer, A. Bruhn, J. Weickert:
    Freehand HDR imaging of moving scenes with simultaneous resolution enhancement.
    Computer Graphics Forum (Proc.of Eurographics), Vol. 30, No. 2, 405-414, April 2011.
    Also available as Technical Report No. 286, Department of Mathematics, Saarland University, Saarbrücken, Germany, December 2010.
  76. See also: Supplementary Material Webpage.

  77. M. Breuß, H. Zimmer, J. Weickert:
    Can variational models for correspondence problems benefit from upwind discretisations?
    Journal of Mathematical Imaging and Vision, Vol. 39, No. 3, 230-244, March 2011.
    Revised version of Technical Report No. 254, Department of Mathematics, Saarland University, Saarbrücken, Germany, December 2009 (revised June 2010).
  78. N. Ludwig, A. Keller, S. Heisel, P. Leidinger, S. Rheinheimer, C. Andres, B. Stephan, W. I. Steudel, E. Donauer, N. Graf, B. Burgeth, J. Weickert, H.-P. Lenhof, E. Meese:
    Novel immunogenic antigens increase classification accuracy in meningioma to 93.84 %.
    International Journal of Cancer, Vol. 128, No. 6, 1493-1501, March 2011.
  79. M. Welk, M. Breuß, O. Vogel:
    Morphological amoebas are self-snakes.
    Journal of Mathematical Imaging and Vision, Vol. 39, No. 2, 87-99, February 2011.
    Revised version of Technical Report No. 259, Department of Mathematics, Saarland University, Saarbrücken, Germany, February 2010.
  80. S. Grewenig, S. Zimmer, J. Weickert:
    Rotationally invariant similarity measures for nonlocal image denoising.
    Journal of Visual Communication and Image Representation, Vol. 22, No. 2, 117-130, February 2011.
    Revised version of Technical Report No. 265, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2010.
  81. T. Teuber, G. Steidl, P. Gwosdek, C. Schmaltz, J. Weickert:
    Dithering by differences of convex functions.
    SIAM Journal on Imaging Sciences, Vol. 4, No. 1, 79-108, January 2011.
    Revised version of Technical Report No. Pr-2010-01, Department of Mathematics, University of Mannheim, Germany, April 2010.
  82. C. Schmaltz, P. Gwosdek, A. Bruhn, J. Weickert:
    Electrostatic halftoning.
    Computer Graphics Forum, Vol. 29, No. 8, 2313-2327, December 2010.
    Revised version of Technical Report No. 260, Department of Mathematics, Saarland University, Saarbrücken, Germany, February 2010.
    See also: Supplementary Material Webpage.
  83. L. Pizarro, P. Mrázek, S. Didas, S. Grewenig, J. Weickert:
    Generalised nonlocal image smoothing.
    International Journal of Computer Vision, Vol. 90, No. 1, 62-87, October 2010.
    Revised version of Technical Report No. 248, Department of Mathematics, Saarland University, Saarbrücken, Germany, Sept. 2009.
  84. S. Grewenig, J. Weickert, A. Bruhn:
    From box filtering to fast explicit diffusion.
    In M. Goesele, S. Roth, A. Kuijper, B. Schiele, K. Schindler (Eds.): Pattern Recognition.
    Lecture Notes in Computer Science, Vol. 6376, 533-542, Springer, Berlin, 2010.
    Awarded the DAGM 2010 Main Prize (Best Paper Award).
  85. M. Carrasco, L. Pizarro, D. Mery:
    Visual inspection of glass bottlenecks by multiple-view analysis.
    International Journal of Computer Integrated Manufacturing, Vol. 23, No. 10, 925-941, Sept. 2010.
  86. L. Valgaerts, A. Bruhn, H. Zimmer, J. Weickert, C. Stoll, C. Theobalt:
    Joint estimation of motion, structure and geometry from stereo sequences.
    In K. Daniilidis, P. Maragos, N. Paragios (Eds.): Computer Vision - ECCV 2010. Lecture Notes in Computer Science, Vol. 6314, 568-581, Springer, Berlin, 2010.
    See also: Supplementary Material Webpage.
  87. P. Gwosdek, A. Bruhn, J. Weickert:
    Variational optic flow on the Sony PlayStation 3 – Accurate dense flow fields for real-time applications.
    Journal of Real-Time Image Processing, Vol. 5, No. 3, 163-177, September 2010.
    Revised version of Technical Report No. 233, Department of Mathematics, Saarland University, Saarbrücken, Germany, March 2009.
  88. M. Breuß, O. Vogel, K. U. Hagenburg:
    Newton interpolation with extremely high degrees by Leja ordering and fast Leja points.
    Technical Report No. 273, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2010.
  89. S. Didas, G. Steidl, J. Weickert:
    Integrodifferential equations for multiscale wavelet shrinkage: The discrete case.
    International Journal of Electrical and Computer Engineering Systems, Vol. 1, No. 1, 5-21, May 2010.
    Revised version of Technical Report No. 214, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2008.
  90. C. Hauger, H. Weigand, J. Weickert, A. Bruhn:
    Medizinisch optisches Beobachtungsgerät und Verfahren zum Erstellen einer stereoskopischen Zwischenperspektive in einem derartigen Gerät.
    Patent DE 10 2008 024 732 B4 2010.04.01, April 2010.
  91. M. Welk:
    Robust variational approaches to positivity-constrained image deconvolution.
    Technical Report No. 261, Department of Mathematics, Saarland University, Saarbrücken, Germany, March 2010.
  92. T. Brox, M. Rousson, R. Deriche, J. Weickert:
    Colour, texture, and motion in level set based segmentation and tracking.
    Image and Vision Computing, Vol. 28, No. 3, 376-390, March 2010.
    Revised version of Technical Report No. 147, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  93. E. Bae, J. Weickert:
    Partial differential equations for interpolation and compression of surfaces.
    In M. Daehlen, M. Floater, T. Lyche, J.-L. Merrien, K. Mørken, L. L. Schumaker (Eds.): Mathematical Methods for Curves and Surfaces. Lecture Notes in Computer Science, Vol. 5862, 1-14, Springer, Berlin, 2010.
  94. N. Ludwig, A. Keller, S. Heisel, P. Leidinger, V. Klein, S. Rheinheimer, C. Andres, B. Stephan, W. I. Steudel, N. Graf, B. Burgeth, J. Weickert, H.-P. Lenhof, E. Meese:
    Improving seroreactivity based detection of glioma.
    Neoplasia, Vol. 11, No. 12, 1383-1389, Dec. 2009.
  95. K. Hagenburg, M. Breuß, O. Vogel, J. Weickert, M. Welk:
    A lattice Boltzmann model for rotationally invariant dithering.
    In G. Bebis, R. Boyle, B. Parvin, D. Koracin, Y. Kuno, J. Wang, R. Pajarola, P. Lindstrom, A. Hinkenjann, M. L. Encarnaçao, C. T. Silva, D. Coming (Eds.): Advances in Visual Computing. Lecture Notes in Computer Science, Vol. 5876, 949-959, Springer, Berlin, 2009.
  96. M. Breuß:
    Monotonicity of implicit finite difference methods for hyperbolic conservation laws.
    Technical Report No. 253, Department of Mathematics, Saarland University, Saarbrücken, Germany, November 2009.
  97. S. Didas, J. Weickert, B. Burgeth:
    Properties of higher order nonlinear diffusion filtering.
    Journal of Mathematical Imaging and Vision, Vol. 35, 208-226, 2009.
    Revised version of Technical Report No. 215, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2008.
  98. M. Breuß, E. Cristiani, J.-D. Durou, M. Falcone, O. Vogel:
    Numerical algorithms for perspective shape from shading.
    Technical Report No. 240, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2009.
  99. M. Breuß, D. Dietrich:
    Fuzzy numerical schemes for hyperbolic differential equations.
    In B. Mertsching, M. Hund, Z. Aziz (Eds.): KI 2009: Advances in Artificial Intelligence. Lecture Notes in Computer Science, Vol. 5803, 419-426, © Springer-Verlag Berlin Heidelberg 2009.
  100. A. Keller, N. Ludwig, S. Heisel, P. Leidinger, C. Andres, W.-I. Steudel, H. Huwer, B. Burgeth, M. Hein, J. Weickert, E. Meese, H.-P. Lenhof:
    Large-scale antibody profiling of human blood sera: The future of molecular diagnosis.
    Informatik Spektrum, Vol. 32, No. 4, 332-338, 2009.
  101. H. Zimmer, A. Bruhn, J. Weickert, L. Valgaerts, A. Salgado, B. Rosenhahn, H.-P. Seidel:
    Complementary optic flow.
    In D. Cremers, Y. Boykov, A. Blake, F. R. Schmidt (Eds.): Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science, Vol. 5681, 207-220, Springer, Berlin, 2009.
  102. M. Mainberger and J. Weickert:
    Edge-based image compression with homogeneous diffusion.
    In X. Jiang, N. Petkov (Eds.): Computer Analysis of Images and Patterns. Lecture Notes in Computer Science, Vol. 5702, Springer, Berlin, 476-483, 2009.
  103. O. Vogel, L. Valgaerts, M. Breuß, and J. Weickert:
    Making shape from shading work for real-world images.
    In J. Denzler, G. Notni, H. Süße (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 5748, 191-200, Springer, Berlin, 2009
  104. C. Schmaltz, B. Rosenhahn, T. Brox, and J. Weickert:
    Localised mixture models in region-based tracking.
    In J. Denzler, G. Notni, H. Süße (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 5748, 21-30, Springer, Berlin, 2009
  105. C. Schmaltz, J. Weickert, and A. Bruhn:
    Beating the quality of JPEG 2000 with anisotropic diffusion.
    In J. Denzler, G. Notni, H. Süße (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 5748, 452-461, Springer, Berlin, 2009
  106. L. Pizarro, B. Burgeth, M. Breuß, J. Weickert:
    A directional Rouy-Tourin scheme for adaptive matrix-valued morphology.
    In M. H. F. Wilkinson, J. B. T. M. Roerdink (Eds.): Mathematical Morphology and Its Application to Signal and Image Processing. Lecture Notes in Computer Science, Vol. 5720, 250-260, Springer, Berlin, 2009.
  107. M. Welk, M. Breuß, O. Vogel:
    Differential equations for morphological amoebas.
    Updated with an erratum. – In M. H. F. Wilkinson, J. B. T. M. Roerdink (Eds.): Mathematical Morphology and Its Application to Signal and Image Processing. Lecture Notes in Computer Science, vol. 5720, 104–114, Springer, Berlin, 2009.
  108. Z. Belhachmi, D. Bucur, B. Burgeth, J. Weickert:
    How to choose interpolation data in images.
    SIAM Journal on Applied Mathematics, Vol. 70, No. 1, 333-352, 2009.
    Revised version of Technical Report No. 205, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2008.
  109. M. Backes, T. Chen, M. Dürmuth, H. Lensch, M. Welk:
    Tempest in a teapot: compromising reflections revisited.
    Proc. 30th IEEE Symposium on Security and Privacy, Oakland, USA, 315–327. IEEE Computer Society, 2009.
  110. M. Ghodstinat, A. Bruhn, J. Weickert:
    Deinterlacing with motion-compensated anisotropic diffusion.
    In D. Cremers, B. Rosenhahn, A. Yuille, F. Schmidt (Eds.): Statistical and Geometrical Approaches to Visual Motion Analysis. Lecture Notes in Computer Science, Vol. 5604, 91-106, Springer, Berlin, 2009.
  111. S. Barbieri, M. Welk, J. Weickert:
    A variational approach to the registration of tensor-valued images.
    In S. Aja-Fernandez, R. de Luis-Garcia, D. Tao, X. Li (Eds.): Tensors in Image Processing and Computer Vision, 59-77, Springer, London, 2009.
    Revised version of Technical Report No. 221, Department of Mathematics, Saarland University, Saarbrücken, Germany, September 2008.
  112. B. Burgeth, M. Breuß, S. Didas, J. Weickert:
    PDE-based morphology for matrix fields: Numerical solution schemes.
    In S. Aja-Fernandez, R. de Luis-Garcia, D. Tao, X. Li (Eds.): Tensors in Image Processing and Computer Vision, 125-150, Springer, London, 2009.
    Revised version of Technical Report No. 220, Department of Mathematics, Saarland University, Saarbrücken, Germany, September 2008.
  113. M. Breuß, J. Weickert:
    Highly accurate PDE-based morphology for general structuring elements.
    In X.-C. Tai, K. Mørken, M. Lysaker, K.-A. Lie (Eds.): Scale-Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science, Vol. 5567, 758-769, Springer, Berlin, 2009.
  114. B. Burgeth, M. Breuß, L. Pizarro, J. Weickert:
    PDE-driven adaptive morphology for matrix fields.
    In X.-C. Tai, K. Mørken, M. Lysaker, K.-A. Lie (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 5567, 247-258, Springer, Berlin, 2009.
  115. M. Welk, G. Gilboa, J. Weickert:
    Theoretical foundations for discrete forward-and-backward diffusion filtering.
    In X.-C. Tai, K. Mørken, M. Lysaker, K.-A. Lie (Eds.): Scale-Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science, vol. 5567, 527–538. Springer, Berlin, 2009.
  116. O. Vogel, M. Breuß, T. Leichtweis, J. Weickert:
    Fast shape from shading for Phong-type surfaces.
    In X.-C. Tai, K. Mørken, M. Lysaker, K.-A. Lie (Eds.): Scale-Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science, vol. 5567, 733-744. Springer, Berlin, 2009.
  117. H. Zimmer, M. Breuß, J. Weickert, H.-P. Seidel:
    Hyperbolic numerics for variational approaches to correspondence problems.
    In X.-C. Tai, K. Mørken, M. Lysaker, K.-A. Lie (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 5567, 636-647, Springer, Berlin, 2009.
  118. D. H. Laidlaw, J. Weickert (Eds.):
    Visualization and Processing of Tensor Fields: Advances and Perspectives
    Springer, Berlin, 2009.
  119. T. Schultz, J. Weickert, H.-P. Seidel:
    A higher-order structure tensor.
    In D. H. Laidlaw, J. Weickert (Eds.): Visualization and Processing of Tensor Fields: Advances and Perspectives. Springer, Berlin, 263-279, 2009.
    Revised version of Research Report MPI-I-2007-4-005, Max-Planck-Institut für Informatik, Saarbrücken, Germany, July 2007.
  120. B. Burgeth, S. Didas, J. Weickert:
    A general structure tensor concept and coherence-enhancing diffusion filtering for matrix fields.
    In D. H. Laidlaw, J. Weickert (Eds.): Visualization and Processing of Tensor Fields: Advances and Perspectives. Springer, Berlin, 305-323, 2009.
    Revised version of Technical Report No. 197, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2007.
  121. S. Setzer, G. Steidl, B. Popilka, B. Burgeth:
    Variational methods for denoising matrix fields.
    In D. H. Laidlaw, J. Weickert (Eds.): Visualization and Processing of Tensor Fields: Advances and Perspectives. Springer, Berlin, 341-360, 2009.
  122. J. Lie, B. Burgeth, O. Christiansen:
    An operator algebraic inverse scale space method for symmetric matrix valued images.
    In D. H. Laidlaw, J. Weickert (Eds.): Visualization and Processing of Tensor Fields: Advances and Perspectives. Springer, Berlin, 361-376, 2009.
  123. M. Breuß, O. Vogel, J. Weickert:
    Efficient numerical techniques for perspective shape from shading.
    In A. Handlovicova, P. Frolkovic, K. Mikula, D. Sevcovic (Eds.): Algoritmy 2009 (Podbanske, Slovakia, March 2009), 11-20, Slovak University of Technology, Bratislava, 2009.
  124. S. Didas, G. Steidl, S. Setzer:
    Combined l_2 data and gradient fitting in conjunction with l_1 regularization.
    Revised version of Preprint No. 143, DFG Priority Programme 1114, Department of Mathematics, University of Bremen, Germany, June 2006.
  125. D. Han, B. Rosenhahn, J. Weickert:
    Combined registration methods for pose estimation.
    In G. Bebis, R. Boyle, B. Parvin, D. Koracin, P. Remagnino, F. Porikli, J. Peters, J. Klosowski, L. Arns, Y. K. Chun, T.-M. Rhyne, L. Monroe (Eds.): Advances in Visual Computing. Lecture Notes in Computer Science, Vol. 5358, 913-924, Springer, Berlin, 2008.
  126. L. Pizarro, B. Burgeth, S. Didas, J. Weickert:
    A generic neighbourhood filtering framework for matrix fields.
    In D. Forsyth, P. Torr, A. Zisserman (Eds.): Computer Vision – ECCV 2008. Lecture Notes in Computer Science, Vol. 5304, 521-532. Springer, Berlin, 2008.
  127. M. Breuß, O. Vogel, J. Weickert:
    Perspective shape from shading for Phong-type non-Lambertian surfaces.
    Technical Report No. 216, Dept. of Mathematics, Saarland University, Saarbrücken, Germany, August 2008.
  128. H. Zimmer, A. Bruhn, L. Valgaerts, M. Breuß, J. Weickert, B. Rosenhahn, H.-P. Seidel:
    PDE-based anisotropic disparity-driven stereo vision.
    In O. Deussen, D. Keim, D. Saupe (Eds.): Vision, Modeling, and Visualization 2008. AKA Heidelberg, 263-272, 2008.
  129. P. Gwosdek, A. Bruhn, J. Weickert:
    High performance parallel optical flow algorithms on the Sony Playstation 3.
    In O. Deussen, D. Keim, D. Saupe (Eds.): Vision, Modeling, and Visualization 2008, AKA, Heidelberg, 253-262, October 2008.
  130. L. Wietzke, G. Sommer, C. Schmaltz, J. Weickert:
    Analysis of the curvature tensor from the viewpoint of signal processing.
    In T. E. Simos, G. Maroulis, G. Psihoyios, C. Tsitouras (Eds.): Selected Papers from ICNAAM-2007 and ICCMSE-2007. AIP Conference Proceedings, Vol. 1046, 150-153, American Institute of Physics, Melville, 2008.
  131. M. Carrasco, L. Pizarro, D. Mery:
    Image acquisition and automated inspection of wine bottlenecks by tracking in multiple views.
    Proc. of the 8th International Conference on Signal Processing, Computational Geometry and Artificial Vision - ISCGAV 2008, 84-89, August 2008.
  132. S. Zimmer, S. Didas, J. Weickert:
    A rotationally invariant block matching strategy improving image denoising with non-local means.
    Proc. 2008 International Workshop on Local and Non-Local Approximation in Image Processing (August 2008, Lausanne, Switzerland).
  133. S. Barbieri, M. Welk, J. Weickert:
    Variational registration of tensor-valued images.
    Proc. CVPR Workshop »Tensors in Image Processing and Computer Vision«, Anchorage, Alaska, USA, 23 June 2008, pages 1-6.
  134. M. Krause, R. M. Alles, B. Burgeth, J. Weickert:
    Retinal vessel detection via second derivative of local Radon transform
    Technical Report No. 212, Department of Mathematics, Saarland University, Saarbrücken, Germany, June 2008.
  135. O. Vogel, M. Breuß, J. Weickert:
    Perspective shape from shading with non-Lambertian reflectance.
    In G. Rigoll (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 5096, 517-526, Springer, Berlin, 2008.
  136. C. Schmaltz, B. Rosenhahn, T. Brox, J. Weickert, L. Wietzke, G. Sommer:
    Dealing with self-occlusion in region based motion capture by means of internal regions.
    In F. J. Perales, R. B. Fischer (Eds.): Articulated Motion and Deformable Objects. Lecture Notes in Computer Science, Vol. 5098, 102-111, Springer, Heidelberg, 2008.
  137. I. Galić, J. Weickert, M. Welk, A. Bruhn, A. Belyaev, H.-P. Seidel:
    Image compression with anisotropic diffusion.
    Journal of Mathematical Imaging and Vision, Vol. 31, 255–269, 2008. Invited Paper.
  138. B. Rosenhahn, C. Schmaltz, T. Brox, J. Weickert, D. Cremers, H.-P. Seidel:
    Markerless motion capture of man-machine interaction.
    Proc. 2008 IEEE Conference of Computer Vision and Pattern Recognition (Anchorage, AK, June 2008). IEEE Computer Society Press, 2008.
  139. S. Didas, G. Steidl, J. Weickert:
    Discrete multiscale wavelet shrinkage and integrodifferential equations.
    In P. Schelkens, T. Ebrahimi, G. Christobal, F. Truchetet (Eds.): Optical and Digital Image Processing - Photonics Europe. SPIE Vol. 7000, 2008.
  140. L. Valgaerts, A. Bruhn, J. Weickert:
    A variational approach for the joint recovery of the optical flow and the fundamental matrix.
    In G. Rigoll (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 5096, 314-324, Springer, Berlin, 2008.
  141. B. Rosenhahn, C. Schmaltz, T. Brox, J. Weickert, H.-P. Seidel:
    Staying well grounded in markerless motion capture.
    In G. Rigoll (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 5096, 385-395, Springer, Berlin, 2008.
  142. M. Mainberger, A. Bruhn, J. Weickert:
    Is dense optical flow useful to compute the fundamental matrix?
    Updated version with errata. In A. Campilho, M. Kamel (Eds.): Image Analysis and Recognition. Lecture Notes in Computer Science, Vol. 5112, 630-639, Springer, Berlin, 2008.
  143. R. Dahlhaus, J. Franke, J. Polzehl, V. Spokoiny, G. Steidl, J. Weickert, A. Berdychevski, S. Didas, S. Halim, P. Mrázek, S. S. Rao, J. Tadjuidje:
    Structural adaptive smoothing procedures.
    In R. Dahlhaus, J. Kurths, P. Maass, J. Timmer (Eds.): Mathematical Methods in Time Series Analysis and Digital Image Processing, Springer, Berlin, 325-339, 2008.
  144. L. Wietzke, G. Sommer, C. Schmaltz, J. Weickert:
    Differential geometry of monogenic signal representations.
    In B. McDonald, U. Franke, R. Klette, G. Sommer (Eds.): Robot Vision. Lecture Notes in Computer Science, Vol. 4931, 454-465, 2008
  145. A. Bruhn:
    Bewegungsschätzung in Echtzeit mit Optimierungsansätzen.
    it - Information Technology, Vol. 50, No. 1, 66-69,
    Oldenbourg Wissenschaftsverlag, 2008.
  146. M. Welk, G. Steidl, J. Weickert:
    Locally analytic schemes: a link between diffusion filtering and wavelet shrinkage.
    Applied and Computational Harmonic Analysis, Vol. 24, 195–224, 2008.
  147. L. Pizarro, D. Mery, R. Delpiano, M. Carrasco:
    Robust automated multiple view inspection
    Pattern Analysis and Applications, Vol. 11, No. 1, 21-32, 2008.
    Revised version of Technical Report No. 192, Department of Mathematics, Saarland University, Saarbrücken, Germany, April 2007.
  148. B. Burgeth, S. Didas, L. Florack, J. Weickert:
    A generic approach to diffusion filtering of matrix-fields.
    Computing, Vol. 81, No. 2-3, 179-197, Nov. 2007. Invited Paper.
  149. H. P. A. Lensch, B. Rosenhahn, H.-P. Seidel, P. Slusallek, J. Weickert (Eds.):
    Vision, Modeling, and Visualization 2007.
    MPI-I Saarbrücken and AKA, Berlin, Nov. 2007.
  150. O. Vogel, M. Breuß, J. Weickert:
    A direct numerical approach to perspective shape-from-shading
    In H. Lensch, B. Rosenhahn, H.-P. Seidel, P. Slusallek, J. Weickert (Eds.): Vision, Modeling, and Visualization 2007. MPI-I Saarbrücken and AKA, Berlin, 91-100, 2007.
  151. I. Sommer, O. Müller, F. S. Domingues, O. Sander, J. Weickert, T. Lengauer:
    Moment invariants as shape recognition technique for comparing protein binding sites.
    Bioinformatics, Vol. 23, No. 23, 3139-3146, Oct. 2007.
  152. T. Schuster, J. Weickert:
    On the application of projection methods for computing optical flow fields.
    Inverse Problems and Imaging, Vol. 1, No. 4, 673-690, 2007.
    Revised version of Technical Report No. 194, Department of Mathematics, Saarland University, Saarbrücken, Germany, May 2007.
  153. M. Carrasco, L. Pizarro, D. Mery:
    Bimodal biometric person identification system under perturbations .
    In D. Mery, L. Rueda (Eds.): Advances in Image and Video Technology, Lecture Notes in Computer Science, Vol. 4872, 114-127, Springer, Berlin, 2007.
  154. C. Schmaltz, B. Rosenhahn, T. Brox, J. Weickert, D. Cremers, L. Wietzke, G. Sommer:
    Occlusion modeling by tracking multiple objects.
    In F. A. Hamprecht, C. Schnörr, B. Jähne (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 4713, 173-183, Springer, Berlin, 2007.
  155. Y. Mileva, A. Bruhn, J. Weickert:
    Illumination-robust variational optical flow with photometric invariants.
    In F. A. Hamprecht, C. Schnörr, B. Jähne (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 4713, 152-162, Springer, Berlin, 2007.
  156. A. Bruhn:
    Variationsansätze zur Bewegungsschätzung: Präzise Modellierung und effiziente Numerik.
    In D. Wagner et al. (Eds.): Ausgezeichnete Informatikdissertationen 2006. GI-Edition Lecture Notes in Informatics (LNI), Vol. D-7, 9-18, Gesellschaft für Informatik, Bonn, 2007.
  157. C. Schmaltz, B. Rosenhahn, T. Brox, D. Cremers, J. Weickert, L. Wietzke, and G. Sommer:
    Region-based pose tracking.
    Technical Report No. 196, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2007.
  158. B. Rosenhahn, T. Brox, J. Weickert:
    Three-dimensional shape knowledge for joint image segmentation and pose tracking.
    International Journal of Computer Vision, Vol. 73, No. 3, 243-262, July 2007.
    Revised version of Technical Report No. 163, Centre for Imaging Technology and Robotics, University of Auckland, New Zealand, 2005.
  159. L. Pizarro, S. Didas, F. Bauer, J. Weickert:
    Evaluating a general class of filters for image denoising
    In B. K. Esbøll, K. S. Pedersen (Eds.): Image Analysis.
    Lecture Notes in Computer Science, Vol. 4522, 601-610, Springer, Berlin, 2007.
  160. N. Slesareva, T. Bühler, K. Hagenburg, J. Weickert, A. Bruhn, Z. Karni, H.-P. Seidel:
    Robust variational reconstruction from multiple views.
    In B. K. Esbøll, K. S. Pedersen (Eds.): Image Analysis.
    Lecture Notes in Computer Science, Vol. 4522, 173-182, Springer, Berlin, 2007.
  161. M. Breuß, B. Burgeth, J. Weickert:
    Anisotropic continuous-scale morphology.
    In J. Martí, J. M. Benedí, A. M. Mendonça, J. Serrat (Eds.): Pattern Recognition and Image Analysis. Part II. Lecture Notes in Computer Science, Vol. 4487, 515-522, Springer, Berlin, 2007.
  162. C. Schmaltz, B. Rosenhahn, T. Brox, D. Cremers, J. Weickert, L. Wietzke, G. Sommer:
    Region-based pose tracking.
    In J. Martí, J. M. Benedí, A. M. Mendonça, J. Serrat (Eds.): Pattern Recognition and Image Analysis. Part II. Lecture Notes in Computer Science, Vol. 4478, 56-63, Springer, Berlin, 2007.
  163. M. Welk, J. G. Nagy:
    Variational deconvolution of multi-channel images with inequality constraints.
    In J. Martí, J. M. Benedí, A. M. Mendonça, J. Serrat (Eds.): Pattern Recognition and Image Analysis. Part I. Lecture Notes in Computer Science, Vol. 4477, 386-393, Springer, Berlin, 2007.
  164. B. Burgeth, S. Didas, L. Florack, J. Weickert:
    A generic approach to the filtering of matrix fields with singular PDEs.
    In F. Sgallari, A. Murli, N. Paragios (Eds.), Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 556-567, Springer, Berlin, 2007.
  165. O. Demetz, J. Weickert, A. Bruhn, M. Welk:
    Beauty with variational methods: An optic flow approach to hairstyle simulation.
    In F. Sgallari, A. Murli, N. Paragios (Eds.), Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 825-836, Springer, Berlin, 2007.
  166. S. Didas, J. Weickert:
    Combining curvature motion and edge-preserving denoising.
    In F. Sgallari, A. Murli, N. Paragios (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 568 - 579, Springer, Berlin, 2007.
  167. D. Zang, L. Wietzke, C. Schmaltz, G. Sommer
    Dense optical flow estimation from the monogenic curvature tensor.
    In F. Sgallari, A. Murli, N. Paragios (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 239 - 250, Springer, Berlin, 2007.
  168. E. Hodneland, X.-C. Tai, J. Weickert, N. Bukoreshtliev, H.-H. Gerdes:
    Level set methods for watershed image segmentation.
    In F. Sgallari, F. Murli, N. Paragios (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 178-190, Springer, Berlin, 2007.
  169. O. Vogel, A. Bruhn, J. Weickert, S. Didas:
    Direct shape-from-shading with adaptive higher order regularisation.
    In F. Sgallari, F. Murli, N. Paragios (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 871-882, Springer, Berlin, 2007.
  170. M. Welk, P. Kim, P. Olver:
    Numerical invariantization for morphological PDE schemes.
    In F. Sgallari, A. Murli, N. Paragios (Eds.), Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 508-519, Springer, Berlin, 2007.
  171. M. Breuß, M. Welk:
    Staircasing in semidiscrete stabilised inverse diffusion algorithms.
    Journal of Computational and Applied Mathematics, Vol. 206, No. 1, 520-533, 2007.
    Revised version of Technical Report No. 165, Department of Mathematics, Saarland University, Saarbrücken, Germany, January 2006.
  172. B. Burgeth, A. Bruhn, S. Didas, J. Weickert, M. Welk:
    Morphology for tensor data: Ordering versus PDE-based approach.
    Image and Vision Computing, Vol. 25, No. 4, 496-511, 2007.
    Revised version of Technical Report No. 162, Department of Mathematics, Saarland University, Saarbrücken, Germany, December 2005.
  173. M. Welk, J. Weickert, I. Galić:
    Theoretical foundations for spatially discrete 1-D shock filtering.
    Image and Vision Computing, Vol. 25, No. 4, 455–463, 2007.
    Revised version of Technical Report No. 150, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  174. P. Mrázek, J. Weickert:
    From two-dimensional nonlinear diffusion to coupled Haar wavelet shrinkage.
    Journal of Visual Communication and Image Representation, Vol. 18, No. 2, 162-175, 2007.
    Revised version of Preprint No. 132, DFG Priority Programme 1114, University of Bremen, Germany, August 2005.
  175. S. Didas, J. Weickert:
    Integrodifferential equations for continuous multiscale wavelet shrinkage.
    Inverse Problems and Imaging, Vol. 1, No. 1, 47-62, 2007.
  176. B. Burgeth, J. Weickert, S. Tari:
    Minimally stochastic schemes for singular diffusion equations.
    In X.-C. Tai, K.-A. Lie, T. F. Chan, S. Osher (Eds.): Image Processing Based on Partial Differential Equations, 325-339, Springer, Berlin, 2007.
  177. B. Burgeth, N. Papenberg, A. Bruhn, M. Welk, J. Weickert:
    Mathematical morphology for matrix fields induced by the Loewner ordering in higher dimensions.
    Signal Processing, Vol. 87, No. 2, 277-290, February 2007.
    Revised version of Technical Report No. 161, Department of Mathematics, Saarland University, Saarbrücken, Germany, December 2005.
  178. M. Welk, J. Weickert, F. Becker, C. Schnörr, C. Feddern, B. Burgeth:
    Median and related local filters for tensor-valued images.
    Signal Processing, Vol. 87, No. 2, 291-308, February 2007.
    Revised version of Technical Report No. 135, Department of Mathematics, Saarland University, Saarbrücken, Germany, April 2005.
  179. Y.-J. Kim, T. Brox, W. Feiden, J. Weickert:
    Fully automated segmentation and morphometrical analysis of muscle fibre images.
    Cytometry: Part A, Vol. 71A, No. 1, 8-15, 2007.
    Revised version of Technical Report No. 177, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2006.
  180. R. Kimmel, N. Sochen, J. Weickert (Eds.):
    Scale Space and PDE Methods in Computer Vision.
    Special Issue of International Journal of Computer Vision, Vol. 70, No. 3, Dec. 2006.
  181. T. Schultz, B. Burgeth, J. Weickert:
    Flexible segmentation and smoothing of DT-MRI fields through a customizable structure tensor.
    In G. Bebis, R. Boyle, B. Parvin, D. Koracin, P. Remagnino, A. V. Nefian, M. Gopi, V. Pascucci, J. Zara, J. Molineros, H. Theisel, T. Malzbender (Eds.): Advances in Visual Computing. Lecture Notes in Computer Science, Vol. 4291, Springer, 454-464, 2006.
    Awarded the ISVC 2006 Best Paper Award.
  182. S. Didas, P. Mrázek, J. Weickert:
    Energy-based image simplification with nonlocal data and smoothness terms.
    In A. Iske, J. Levesley (Eds.): Algorithms for Approximation, 50-60, Springer, Heidelberg, 2006.
  183. A. Bruhn, J. Weickert, T. Kohlberger, C. Schnörr:
    A multigrid platform for real-time motion computation with discontinuity-preserving variational methods.
    International Journal of Computer Vision, Vol. 70, No. 3, 257-277, December 2006.
  184. T. Brox, J. Weickert:
    A TV flow based local scale estimate and its application to texture discrimination.
    Journal of Visual Communication and Image Representation, Vol. 17, No. 5, 1053-1073, October 2006.
    Revised version of Technical Report No. 134, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  185. M. Breuß, J. Weickert:
    A shock-capturing algorithm for the differential equations of dilation and erosion.
    Journal of Mathematical Imaging and Vision, Vol. 25, 187-201, 2006.
    Revised version of Technical Report No. 153, Department of Mathematics, Saarland University, Saarbrücken, Germany, September 2005.
  186. T. Brox, J. Weickert:
    Level set segmentation with multiple regions.
    IEEE Transactions on Image Processing, Vol. 15, No. 10, 3213-3218, October 2006.
    Revised version of Technical Report No. 145, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  187. S. Didas, J. Weickert:
    From adaptive averaging to accelerated nonlinear diffusion filtering.
    In K. Franke, K.-R. M¨ller, B. Nickolay (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 4174, 101-110, Springer, Berlin, 2006.
  188. G. Steidl, S. Didas, J. Neumann:
    Splines in higher order TV regularization.
    International Journal of Computer Vision, Vol. 70, No. 3, 241-255, 2006.
    Revised version of Preprint No. 142, DFG Priority Programme 1114, Department of Mathematics, University of Bremen, Germany, June 2006.
  189. J. Weickert, A. Bruhn, T. Brox, N. Papenberg:
    A survey on variational optic flow methods for small displacements.
    In O. Scherzer (Ed.): Mathematical Models for Registration and Applications to Medical Imaging. 103-136, Springer, Berlin, 2006.
    Also available as Technical Report No. 152, Department of Mathematics, Saarland University, Saarbrücken, Germany, September 2005.
  190. C. Feddern, J. Weickert, B. Burgeth, M. Welk:
    Curvature-driven PDE methods for matrix-valued images.
    International Journal of Computer Vision, Vol. 69, No. 1, 91-103, Aug. 2006.
    Revised version of Technical Report No. 104, Department of Mathematics, Saarland University, Saarbrücken, Germany, April 2004.
  191. N. Papenberg, A. Bruhn, T. Brox, S. Didas, J. Weickert:
    Highly accurate optic flow computation with theoretically justified warping.
    International Journal of Computer Vision, Vol. 67, No. 2, 141-158, April 2006.
    Revised version of Technical Report No. 124, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  192. T. Brox, A. Bruhn, J. Weickert:
    Variational motion segmentation with level sets.
    In H. Bischof, A. Leonardis, A. Pinz (Eds.): Computer Vision – ECCV 2006. Lecture Notes in Computer Science, Vol. 3951, 471–483. Springer, Berlin, 2006.
  193. M. Welk, J. Weickert, G. Steidl:
    From tensor-driven diffusion to anisotropic wavelet shrinkage.
    In H. Bischof, A. Leonardis, A. Pinz (Eds.): Computer Vision – ECCV 2006. Lecture Notes in Computer Science, Vol. 3951, 391–403. Springer, Berlin, 2006.
  194. T. Brox, Y.-J. Kim, J. Weickert, W. Feiden:
    Fully-automated analysis of muscle fiber images with combined region and edge based active contours.
    In H. Handels, J. Ehrhardt, A. Horsch, H. P. Meinzer, T. Tolxdorff (Eds.): Bildverarbeitung in der Medizin. Springer, Berlin, 86-90, 2006.
  195. M. Breuß, M. Welk:
    A conservative shock filter model for the numerical approximation of conservation laws.
    Applied Mathematics Letters, Vol. 19, 954-959, 2006.
    Revised version of Technical Report No. 157, Department of Mathematics, Saarland University, Saarbrücken, Germany, November 2005.
  196. T. Brox, J. Weickert, B. Burgeth, P. Mrázek:
    Nonlinear structure tensors.
    Image and Vision Computing, Vol. 24, No. 1, 41-55, Jan. 2006.
    Revised version of Technical Report No. 113, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2004.
  197. J. Weickert, H. Hagen (Eds.):
    Visualization and Processing of Tensor Fields.
    Springer, Berlin, 2006.
  198. T. Brox, R. van den Boomgaard, F. Lauze, J. van de Weijer, J. Weickert, P. Mrázek, P. Kornprobst:
    Adaptive structure tensors and their applications.
    In J. Weickert, H. Hagen (Eds.): Visualization and Processing of Tensor Fields, 17-47, Springer, Berlin, 2006.
    Revised version of Technical Report No. 141, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  199. B. Burgeth, M. Welk, C. Feddern, J. Weickert:
    Mathematical morphology on tensor data using the Loewner ordering.
    In J. Weickert, H. Hagen (Eds.): Visualization and Processing of Tensor Fields. Mathematics and Visualization, 357-367, Springer, Berlin, 2006.
    Revised version of Technical Report No. 160, Department of Mathematics, Saarland University, Saarbrücken, Germany, December 2005.
  200. J. Weickert, M. Welk:
    Tensor field interpolation with PDEs.
    In J. Weickert, H. Hagen (Eds.): Visualization and Processing of Tensor Fields, 315-325, Springer, Berlin, 2006.
    Revised version of Technical Report No. 142, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  201. J. Weickert, C. Feddern, M. Welk, B. Burgeth, T. Brox:
    PDEs for tensor image processing.
    In J. Weickert, H. Hagen (Eds.): Visualization and Processing of Tensor Fields, 399-414, Springer, Berlin, 2006.
    Revised version of Technical Report No. 143, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2005.
  202. M. Welk, C. Feddern, B. Burgeth, J. Weickert:
    Tensor median filtering and M-smoothing.
    In J. Weickert, H. Hagen (Eds.): Visualization and Processing of Tensor Fields, 345-356, Springer, Berlin, 2006.
  203. M. Breuß, T. Brox, A. Bürgel, T. Sonar, J. Weickert:
    Numerical aspects of TV flow.
    Numerical Algorithms, Vol. 41, No. 1, 79-101, 2006.
    Revised version of Technical Report No. 148, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2005.
  204. J. Weickert, G. Steidl, P. Mrázek, M. Welk, T. Brox:
    Diffusion filters and wavelets: What can they learn from each other?
    In N. Paragios, Y. Chen, O. Faugeras (Eds.): Handbook of Mathematical Models in Computer Vision. 3-16, Springer, New York, 2006.
    Also available as Preprint No. 77, DFG Priority Programme 1114, University of Bremen, Germany, January 2005.
  205. R. Klette, R. Kozera, L. Noakes, J. Weickert (Eds.):
    Geometric Properties from Incomplete Data.
    Springer, Dordrecht, 2006.
  206. A. Bruhn, J. Weickert:
    A confidence measure for variational optic flow methods.
    In R. Klette, R. Kozera, L. Noakes, J. Weickert (Eds.): Geometric Properties from Incomplete Data, 283-297, Springer, Dordrecht, 2006.
    Revised version of Technical Report No. 106, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2004.
  207. P. Mrázek, J. Weickert, A. Bruhn:
    On robust estimation and smoothing with spatial and tonal kernels.
    In R. Klette, R. Kozera, L. Noakes, J. Weickert (Eds.): Geometric Properties from Incomplete Data, 335-352, Springer, Dordrecht, 2006.
    Revised version of Preprint No. 51, DFG Priority Programme 1114, University of Bremen, Germany, June 2004.
  208. B. Burgeth, S. Didas, J. Weickert:
    The Bessel scale-space.
    In O. F. Olsen, L. Florack, A. Kuijper (Eds.): Deep Structure, Singularities, and Computer Vision. Lecture Notes in Computer Science, Vol. 3753, 84-95, Springer, Berlin, 2005.
  209. P. Mrázek, J. Weickert, G. Steidl:
    Diffusion-inspired shrinkage functions and stability results for wavelet denoising.
    International Journal of Computer Vision, Vol. 64, No. 2/3, 171-186, Sept. 2005.
  210. T. Brox, B. Rosenhahn, J. Weickert:
    Three-dimensional shape knowledge for joint image segmentation and pose estimation.
    In W. Kropatsch, R. Sablatnig, A. Hanbury (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 3663, 109-116, Springer, Berlin, 2005.
  211. S. Didas, J. Weickert, B. Burgeth:
    Stability and local feature enhancement of higher order nonlinear diffusion filtering.
    In W. Kropatsch, R. Sablatnig, A. Hanbury (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 3663, 451-458, Springer, Berlin, 2005.
  212. B. Rosenhahn, U. Kersting, D. Smith, J. Gurney, T. Brox, R. Klette:
    A system for marker-less human motion estimation.
    In W. Kropatsch, R. Sablatnig, A. Hanbury (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 3663, 230-237, Springer, Berlin, 2005.
    Awarded the DAGM 2005 Best Paper Award (Main Prize).
  213. N. Slesareva, A. Bruhn, J. Weickert:
    Optic flow goes stereo: A variational method for estimating discontinuity-preserving dense disparity maps.
    In W. Kropatsch, R. Sablatnig, A. Hanbury (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 3663, 33-40, Springer, Berlin, 2005.
    Awarded a DAGM 2005 Paper Prize.
  214. M. Welk, D. Theis, J. Weickert:
    Variational deblurring of images with uncertain and spatially variant blurs.
    In W. Kropatsch, R. Sablatnig, A. Hanbury (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 3663, 485-492, Springer, Berlin, 2005.
  215. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Domain decomposition for variational optical flow computation..
    IEEE Transactions on Image Processing, Vol. 14, No. 8, 1125-1137, August 2005.
  216. B. Rosenhahn, U. Kersting, L. He, A. Smith, T. Brox, R. Klette, H.-P. Seidel:
    A silhouette based human motion tracking system.
    Technical Report No. 164, Centre for Imaging Technology and Robotics, University of Auckland, New Zealand, 2005.
  217. I. Galić, J. Weickert, M. Welk, A. Bruhn, A. Belyaev, H.-P. Seidel:
    Towards PDE-based image compression.
    In N. Paragios, O. Faugeras, T. Chan, C. Schnörr (Eds.): Variational, Geometric, and Level Set Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3752, Springer, Berlin, 37-48, 2005.
  218. A. Bruhn, J. Weickert:
    Towards ultimate motion estimation: Combining highest accuracy with real-time performance.
    In Proc. Tenth IEEE International Conference on Computer Vision, Vol. 1, 749-755, IEEE Computer Society Press, 2005.
  219. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Domain decomposition for nonlinear problems: a control-theoretic approach.
    Technical Report 2005/3, Computer Science Series, University of Mannheim, April 2005.
  220. A. Bruhn, J. Weickert, C. Feddern, T. Kohlberger, C. Schnörr:
    Variational optic flow computation in real-time.
    IEEE Transactions on Image Processing, Vol. 14, No. 5, 608-615, May 2005.
    Revised version of Technical Report No. 89, Department of Mathematics, Saarland University, Saarbrücken, Germany, June 2003.
  221. B. Burgeth, J. Weickert:
    An explanation for the logarithmic connection between linear and morphological system theory.
    International Journal of Computer Vision, Vol. 64, No. 2/3, 157-169, Sept. 2005.
    Revised version of Technical Report No. 95, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2003.
  222. B. Burgeth, N. Papenberg, A. Bruhn, M. Welk, C. Feddern, J. Weickert:
    Morphology for higher-dimensional tensor data via Loewner ordering.
    In C. Ronse, L. Najman, E. Decencière (Eds.): Mathematical Morphology: 40 Years On. Computational Imaging and Vision, Vol. 30, Springer, Dordrecht, 407–416, 2005.
  223. M. Welk, J. Weickert:
    Semidiscrete and discrete well-posedness of shock filtering.
    In C. Ronse, L. Najman, E. Decencière (Eds.): Mathematical Morphology: 40 Years On. Computational Imaging and Vision, Vol. 30, Springer, Dordrecht, 311–320, 2005.
  224. R. Kimmel, N. Sochen, J. Weickert (Eds.):
    Scale-Space and PDE Methods in Computer Vision.
    Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 2005.
  225. M. Breuß, T. Brox, T. Sonar, J. Weickert:
    Stabilised nonlinear inverse diffusion for approximating hyperbolic PDEs.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 536-547, 2005.
  226. A. Bruhn, J. Weickert, T. Kohlberger, C. Schnörr:
    Discontinuity-preserving computation of variational optic flow in real-time.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 279-290, 2005.
  227. B. Burgeth, S. Didas, J. Weickert:
    Relativistic scale-spaces.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 2005.
  228. S. Didas, B. Burgeth, A. Imiya, J. Weickert:
    Regularity and scale-space properties of fractional high order linear filtering.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 2005.
  229. G. Steidl, S. Didas, J. Neumann:
    Relations between higher order TV regularization and support vector regression.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 2005.
  230. M. Welk, F. Becker, C. Schnörr, J. Weickert:
    Matrix-valued filters as convex programs.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 204–216, 2005.
  231. M. Welk, A. Bergmeister, J. Weickert:
    Denoising of audio data by nonlinear diffusion.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 598–609, 2005.
  232. M. Welk, D. Theis, T. Brox, J. Weickert:
    PDE-based deconvolution with forward-backward diffusivities and diffusion tensors.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 585–597, 2005.
  233. M. Welk, J. Weickert, G. Steidl:
    A four-pixel scheme for singular differential equations.
    In R. Kimmel, N. Sochen, J. Weickert (Eds.): Scale-Space and PDE Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 3459, Springer, Berlin, 610–621, 2005.
  234. A. Bruhn, J. Weickert, C. Schnörr:
    Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods. Updated version with errata.
    International Journal of Computer Vision, Vol. 61, No. 3, 211-231, February/March 2005.
  235. T. Brox, J. Weickert:
    Level set based image segmentation with multiple regions.
    In C. E. Rasmussen, H. H. Bülthoff, M. A. Giese, B. Schölkopf (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 3175, Springer, Berlin, 415-423, 2004.
  236. G. Steidl, J. Weickert, T. Brox, P. Mrázek and M. Welk:
    On the equivalence of soft wavelet shrinkage, total variation diffusion, total variation regularization, and SIDEs.
    SIAM Journal on Numerical Analysis, Vol. 42, No. 2, 686-713, 2004.
    An extended version appeared as Technical Report No. 94, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2003.
  237. T. Brox, A. Bruhn, N. Papenberg, J. Weickert:
    High accuracy optical flow estimation based on a theory for warping.
    In T. Pajdla, J. Matas (Eds.): Computer Vision - ECCV 2004. Lecture Notes in Computer Science, Vol. 3024, Springer, Berlin, 25-36, 2004.
    Awarded the "Longuet-Higgins Prize" of ECCV 2004 (Best Paper Award).
  238. T. Brox, J. Weickert:
    A TV flow based local scale measure for texture discrimination.
    In T. Pajdla, J. Matas (Eds.): Computer Vision - ECCV 2004. Lecture Notes in Computer Science, Vol. 3022, Springer, Berlin, 578-590, 2004.
  239. B. Burgeth, M. Welk, C. Feddern, J. Weickert:
    Morphological operations on matrix-valued images.
    In T. Pajdla, J. Matas (Eds.): Computer Vision - ECCV 2004. Lecture Notes in Computer Science, Vol. 3024, Springer, Berlin, 155-167, 2004.
  240. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Parallel variational motion estimation by domain decomposition and cluster computing..
    In T. Pajdla, J. Matas (Eds.): Computer Vision - ECCV 2004. Lecture Notes in Computer Science, Vol. 3024, Springer, Berlin, 205-216, 2004.
  241. A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger, J. Weickert, U. Brüning, C. Schnörr:
    High performance cluster computing with 3-D nonlinear diffusion filters.
    Real-Time Imaging, Vol. 10, No. 1, 41-51, 2004.
    Revised version of Technical Report No. 87, Department of Mathematics, Saarland University, Saarbrücken, Germany, 2003.
  242. N. Papenberg, A. Bruhn, T. Brox, J. Weickert:
    Numerical justification for multiresolution optical flow computation.
    In L. Alvarez (Ed.): IWCVIA '03: International Workshop on Computer Vision and Image Analysis. Vol. 0026 of Cuadernos del Instituto Universitario de Ciencias y Tecnologias Ciberneticas, University of Las Palmas de Gran Canaria, Spain, 7-12, Feb. 2004.
  243. J. Weickert, A. Bruhn, N. Papenberg, T. Brox:
    Variational optic flow computation: From continuous models to algorithms.
    In L. Alvarez (Ed.): IWCVIA '03: International Workshop on Computer Vision and Image Analysis. Vol. 0026 of Cuadernos del Instituto Universitario de Ciencias y Tecnologias Ciberneticas, University of Las Palmas de Gran Canaria, Spain, 1-6, Feb. 2004.
  244. C. Feddern, J. Weickert, B. Burgeth:
    Level-set methods for tensor-valued images.
    In O. Faugeras, N. Paragios (Eds.): Proc. Second IEEE Workshop on Variational, Geometric and Level Set Methods in Computer Vision. Nice, France, 65-72. INRIA, Oct. 2003.
  245. J. Weickert, G. Kühne:
    Fast methods for implicit active contour models.
    In S. Osher, N. Paragios (Eds.): Geometric Level Set Methods in Imaging, Vision and Graphics. Springer, 2003.
  246. D. Slogsnat, M. Fischer, A. Bruhn, J. Weickert, U. Brüning:
    Low level parallelization of nonlinear diffusion filtering algorithms for cluster computing environments.
    In H. Kosch, L. Böszörményi, H. Hellwagner (Eds.): Euro-Par 2003. Parallel Processing. Lecture Notes in Computer Science, Vol. 2790, Springer, Berlin, 481-490, 2003.
  247. T. Kohlberger, C. Schnörr, A. Bruhn, J. Weickert:
    Domain decomposition for parallel variational optic flow computation.
    In B. Michaelis, G. Krell (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2781, Springer, Berlin, 196-202, 2003.
  248. P. Mrázek, J. Weickert:
    Rotationally invariant wavelet shrinkage.
    In B. Michaelis, G. Krell (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2781, Springer, Berlin, 156-163, 2003.
  249. J. Weickert:
    Coherence-enhancing shock filters.
    In B. Michaelis, G. Krell (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2781, Springer, Berlin, 1-8, 2003.
  250. M. Welk, C. Feddern, B. Burgeth, J. Weickert:
    Median filtering of tensor-valued images.
    In B. Michaelis, G. Krell (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2781, Springer, Berlin, 17-24, 2003.
    Awarded a DAGM 2003 Paper Prize.
  251. T. Brox, M. Rousson, R. Deriche, J. Weickert:
    Unsupervised segmentation incorporating colour, texture, and motion.
    In N. Petkov, M. A. Westenberg (Eds.): Computer Analysis of Images and Patterns. Lecture Notes in Computer Science, Vol. 2756, Springer, Berlin, 353-360, 2003.
  252. A. Bruhn, J. Weickert, C. Feddern, T. Kohlberger and C. Schnörr:
    Real-time optic flow computation with variational methods.
    In N. Petkov, M. A. Westenberg (Eds.): Computer Analysis of Images and Patterns. Lecture Notes in Computer Science, Vol. 2756, Springer, Berlin, 222-229, 2003.
  253. T. Brox, M. Welk, G. Steidl, J. Weickert:
    Equivalence results for TV diffusion and TV regularisation.
    In L. D. Griffin, M. Lillholm (Eds.): Scale Space Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 2695, Springer, Berlin, 86-100, 2003.
  254. B. Burgeth, J. Weickert:
    An explanation for the logarithmic connection between linear and morphological system theory.
    In L. D. Griffin, M. Lillholm (Eds.): Scale Space Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 2695, Springer, Berlin, 325-339, 2003.
  255. P. Mrázek, J. Weickert, G. Steidl:
    Correspondences between wavelet shrinkage and nonlinear diffusion.
    In L. D. Griffin, M. Lillholm (Eds.): Scale Space Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 2695, Springer, Berlin, 101-116, 2003.
  256. M. Welk:
    Families of generalised morphological scale spaces.
    In L. D. Griffin, M. Lillholm (Eds.): Scale Space Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 2695, Springer, Berlin, 770-784, 2003.
  257. P. Mrázek, M. Navara:
    Selection of optimal stopping time for nonlinear diffusion filtering.
    International Journal of Computer Vision, Vol. 52 No. 2/3, 189-203, 2003.
  258. T. Brox, M. Rousson, R. Deriche, J. Weickert:
    Unsupervised segmentation incorporating colour, texture, and motion.
    Technical Report No. 4760, Odyssee, INRIA Sophia-Antipolis, France, 2003.
  259. M. Rousson, T. Brox, R. Deriche:
    Active unsupervised texture segmentation on a diffusion based feature space.
    Technical Report No. 4695, Odyssée, INRIA Sophia-Antipolis, France, 2003.
    Slightly extended version of the conference paper with the same title,
    Proc. 2003 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Vol. 2, 699-704, Madison, WI, 2003.
  260. P. Mrázek, J. Weickert, G. Steidl, M. Welk:
    On iterations and scales of nonlinear filters.
    In O. Drbohlav (Ed.): Computer Vision Winter Workshop 2003, Valtice, Czech Republic, 61-66. Czech Pattern Recognition Society, 2003.
  261. J. Weickert, T. Brox:
    Diffusion and regularization of vector- and matrix-valued images.
    In M. Z. Nashed, O. Scherzer (Eds.): Inverse Problems, Image Analysis, and Medical Imaging. Contemporary Mathematics, Vol. 313, 251-268, AMS, Providence, 2002.
  262. D. Cremers, F. Tischhäuser, J. Weickert, C. Schnörr:
    Diffusion snakes: Introducing statistical shape knowledge into the Mumford-Shah functional.
    International Journal of Computer Vision, Vol. 50, No. 3, 295-313, December 2002.
  263. E. Meijering, W. Niessen, J. Weickert, M. Viergever:
    Diffusion-enhanced visualization and quantification of vascular anomalies in three-dimensional rotational angiography: results of an in-vitro evaluation.
    Medical Image Analysis, Vol. 6, No. 3, 217-235, September 2002.
    Preprint.
  264. T. Brox, J. Weickert:
    Nonlinear matrix diffusion for optic flow estimation,
    In L. Van Gool (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2449, Springer, Berlin, 446-453, 2002.
  265. A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger, J. Weickert, U. Brüning, C. Schnörr:
    Designing 3-D nonlinear diffusion filters for high performance cluster computing.
    In L. Van Gool (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2449, Springer, Berlin, 290-297, 2002.
  266. A. Bruhn, J. Weickert, C. Schnörr:
    Combining the advantages of local and global optic flow methods.
    In L. Van Gool (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2449, Springer, Berlin, 454-462, 2002.
    Awarded a DAGM 2002 Paper Prize.
  267. G. Kühne, J. Weickert, M. Beier, W. Effelsberg:
    Fast implicit active contour models.
    In L. Van Gool (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2449, Springer, Berlin, 133-140, 2002.
  268. G. Steidl, J. Weickert:
    Relations between soft wavelet shrinkage and total variation denoising.
    In L. Van Gool (Ed.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 2449, Springer, Berlin, 198-205, 2002.
  269. J. Sporring, W. Niessen, J. Weickert (Eds.):
    Proceedings of the International Workshop on Growth and Motion in 3D Medical Images.
    3D-Lab, University of Copenhagen, Denmark, 2002. ISBN 87-988979-1-8.
  270. W. Hinterberger, O. Scherzer, C. Schnörr, J. Weickert:
    Analysis of optical flow models in the framework of calculus of variations.
    Numerical Functional Analysis and Optimization, Vol. 23, No. 1/2, 69-89, May 2002
    Revised version of Technical Report No. 8/2001, Computer Science Series, University of Mannheim, Germany, April 2001.
  271. L. Alvarez, R. Deriche, J. Sánchez, J. Weickert:
    Dense disparity map estimation respecting image derivatives: a PDE and scale-space based approach.
    Journal of Visual Communication and Image Representation, Vol. 13, No. 1/2, 3-21, March/June 2002.
    Revised version of Technical Report No. 3874, ROBOTVIS, INRIA Sophia-Antipolis, France, January 2000.
    [Demo]
  272. J. Weickert, H. Scharr:
    A scheme for coherence-enhancing diffusion filtering with optimized rotation invariance.
    Journal of Visual Communication and Image Representation, Vol. 13, No. 1/2, 103-118, March/June 2002.
    Revised and shortened version of Technical Report No. 4/2000, Computer Science Series, University of Mannheim, Germany, February 2000.
  273. W. J. Niessen, K. L. Vincken, J. Weickert, M. A. Viergever:
    Multiscale segmentation of volumetric MR brain images.
    In H. Yan (Ed.): Signal Processing for Magnetic Resonance Imaging and Spectroscopy, Marcel Dekker, New York, 209-238, 2002.
  274. J. Weickert, C. Schnörr:
    A theoretical framework for convex regularizers in PDE-based computation of image motion.
    International Journal of Computer Vision, Vol. 45, No. 3, 245-264, December 2001.
    Revised version of Technical Report No. 13/2000, Computer Science Series, University of Mannheim, Germany, June 2000.

This page only lists publications of the MIA Group that has been founded in November 2001. Earlier publications can be found at the web pages of the individual group members, for example at Joachim Weickert's publication page.


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