Welcome to the homepage of

Stephan Didas

Research Associate

Position: Research Associate Phone: +49-681-302-57355 Fax: +49-681-302-57342 E-mail: didas -at- mia.uni-saarland.de Address: Faculty of Mathematics and Computer Science Saarland University, Building E1 1 (former 36.1) 66041 Saarbrücken, Germany Office: Room 3.15 (Building E1 1, Saarbrücken Campus, visitor information) Office hour: Wednesday, 14:00 - 15:00

• Higher and Fractional Order Diffusion Filters
• Continuous and Discrete Variational Methods for Image Denoising
• Relations between Different Classes of Nonlinear Filters
• Processing of Matrix-Valued Data

• Summer term 2008:
  Seminar Processing of Matrix-Valued Images
  Tutorials to Differential Equations in Image Processing and Computer Vision


• Winter term 2007/2008:
  Lecture Convex Analysis for Visual Computing.


• Winter term 2006/2007:
  Tutorials to Image Processing and Computer Vision.

• IEEE Transactions on Pattern Analysis and Machine Intelligence
• IEEE Transactions on Medical Imaging
• IEEE Transactions on Image Processing
• Electronic Letters on Computer Vision and Image Analysis
• Multiscale Modeling and Simulation
• Image and Vision Computing
• Automatica
• Signal Processing
• Signal Processing: Image Communication
• Pattern Recognition
• Inverse Problems and Imaging
• International Journal on Computer Vision
• Journal of Mathematical Imaging and Vision
• SIAM Journal on Imaging Sciences
• SIAM Journal on Scientific Computing
• numerous conferences

Journal Papers

• S. Didas, S. Setzer, G. Steidl:
  Combined l_2 data and gradient fitting in conjunction with l_1 regularization.
  Advances in Computational Mathematics, 2008, in print.
  Revised version of Preprint No. 143, DFG Priority Programme 1114, Department of Mathematics, University of Bremen, Germany, June 2006.
• B. Burgeth, S. Didas, L. Florack, J. Weickert:
  A generic approach to diffusion filtering of matrix-fields.
  Computing, Vol. 81, 179-197, 2007.
  Revised version of Technical Report No. 191, Department of Mathematics, Saarland University, Saarbrücken, Germany, March 2007.
• S. Didas, J. Weickert:
  Integrodifferential Equations for Continuous Multiscale Wavelet Shrinkage.
  Inverse Problems and Imaging, Vol. 1, No. 1, 47-62, 2007.
  Revised version of Preprint No. 147, DFG Priority Programme 1114, Department of Mathematics, University of Bremen, Germany, September 2006.
• 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, April 2007.
  Revised version of Preprint No. 162, Department of Mathematics, Saarland University, Saarbrücken, Germany, December 2005.
• 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.
• 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.

Book Chapters

• J. Franke, R. Dahlhaus, 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, 2008.

Conference Papers

• L. Pizarro, B. Burgeth, S. Didas, J. Weickert:
  A generic neighbourhood filtering framework for matrix fields.
  Proc. 10th European Conference on Computer Vision (ECCV 2008, October 2008, Marseille, France), accepted for publication.
• 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), in print.
• S. Didas, G. Steidl, J. Weickert:
  Discrete multiscale wavelet shrinkage and integrodifferential equations.
  In P. Schelkens, T. Ebrahimi, G. Christobal, F. Truchetet, Optical and Digital Image Processing - Photonics Europe, Vol. 7000 of Proceedings of SPIE, 70000S-1 - 70000S-12, 2008.
• L. Pizarro, S. Didas, F. Bauer, J. Weickert:
  Evaluating a general class of filters for image denoising.
  In B. K. Ersboll, K. S. Pedersen (Eds.): Image Analysis, Lecture Notes in Computer Science, Vol. 4522, 601 - 610, Springer, Berlin, 2007.
  © Springer-Verlag Berlin Heidelberg 2007.
• 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.
  © Springer-Verlag Berlin Heidelberg 2007.
• O. Vogel, A. Bruhn, J. Weickert, S. Didas:
  Direct Shape-from-Shading with Adaptive Higher Order Regularisation.
  In F. Sgallari, A. Murli, N. Paragios (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 4485, 871 - 882, Springer, Berlin, 2007.
  © Springer-Verlag Berlin Heidelberg 2007.
• B. Burgeth, S. Didas, L. Florack, J. Weickert:
  Singular PDEs for the Processing of Matrix-Valued Data.
  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.
  © Springer-Verlag Berlin Heidelberg 2007.
• 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.
  Revised version of Preprint No. 136, DFG Priority Programme 1114, Department of Mathematics, University of Bremen, Germany, November 2005.
  © Springer-Verlag Heidelberg 2006.
• S. Didas, J. Weickert:
  From adaptive averaging to accelerated nonlinear diffusion filtering.
  K. Franke et al. (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 4174, 101 - 110, Springer, Berlin, 2006.
  © Springer-Verlag Berlin Heidelberg 2006.
• 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.
  © Springer-Verlag Berlin Heidelberg 2005.
• S. Didas, J. Weickert, B. Burgeth:
  Stability and local feature enhancement of higher order nonlinear diffusion filtering.
  In W. Kropatsch, R. Sablatnig and A. Hanbury (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 3663, Springer, Berlin, 2005.
  © Springer-Verlag Berlin Heidelberg 2005.
• 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.
  © Springer-Verlag Berlin Heidelberg 2005.
• 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.
  © Springer-Verlag Berlin Heidelberg 2005.
• 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.
  © Springer-Verlag Berlin Heidelberg 2005.

Technical Reports

• S. Didas, J. Weickert, B. Burgeth:
  Properties of Higher Order Nonlinear Diffusion Filtering.
  Technical Report No. 215, Department of Mathematics, Saarland University, Saarbrücken, Germany, August 2008.
• S. Didas, G. Steidl, J. Weickert:
  Integrodifferential Equations for Multiscale Wavelet Shrinkage: The Discrete Case.
  Technical Report No. 214, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2008.
• B. Burgeth, S. Didas, J. Weickert:
  A general structure tensor concept and coherence-enhancing diffusion filtering for matrix fields.
  Technical Report No. 197, Department of Mathematics, Saarland University, Saarbrücken, Germany, July 2007.

• S. Didas:
  Denoising and enhancement of digital images - variational methods, integrodifferential equations, and wavelets [pdf| ps.gz] ,
  PhD thesis, Dept. of Mathematics, Saarland University, 2008.
• S. Didas:
  Higher order variational methods for noise removal in signals and images [pdf| ps.gz],
  Diplomarbeit, Dept. of Mathematics, Saarland University, 2004.
• S. Didas:
  Synchronisation in the Network-Integrated Multimedia Middleware (NMM) [pdf| ps.gz],
  Fortgeschrittenenpraktikum, Dept. of Computer Science, Saarland University, 2002,
  accepted as Bachelor's thesis, 2004.

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