Welcome to the homepage of

Markus Mainberger

Former Research Assistant

Position:    Former Research Assistant E-mail: mainberger -at- mia.uni-saarland.de (please replace anti-spam -at- by @)

• Image Compression
• Epipolar Geometry Estimation

Conference Papers



1. S. Hoffmann, M. Mainberger, J. Weickert, M. Puhl
   Compression of depth maps with segment-based homogeneous diffusion.
   In Scale-Space and Variational Methods in Computer Vision, Proc. Fourth International Conference
   SSVM 2013, Schloss Seggau, Graz region, Austria, June 2013 - A. Kuijper, T. Pock, K. Bredies, H. Bischof (Eds.)
   Lecture Notes in Computer Science, Vol. 7893, 319-330, Springer, Berlin, 2013.
   
   
2. M. Mainberger, C. Schmaltz, M. Berg, J. Weickert, M. Backes
   Diffusion-Based Image Compression in Steganography.
   In Advances in Visual Computing (Part II), Proc. 8th International Symposium
   ISVC 2012, Rethymnon, Crete, Greece, July 2012 - 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.)
   Lecture Notes in Computer Science, Vol. 7432, 219-228, Springer, Berlin, 2012.
   
   
3. 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 Scale Space and Variational Methods in Computer Vision, Proc. Third International Conference
   SSVM 2011, Ein Gedi, Israel, May/June 2011 - A. M. Bruckstein, B. ter Haar Romeny, A. M. Bronstein, M. M. Bronstein (Eds.)
   Lecture Notes in Computer Science, Vol. 6667, 26-37, Springer, Berlin, 2012.
   
   
4. M. Mainberger and J. Weickert
   Edge-Based Image Compression with Homogeneous Diffusion.
   In Computer Analysis of Images and Patterns, Proc. 13th International Conference
   CAIP 2009, Münster, Germany, September 2009 - X. Jiang, N. Petkov (Eds.)
   Lecture Notes in Computer Science, Vol. 5702, 476-483, Springer, Berlin, 2009.
   
   
5. M. Mainberger, A. Bruhn, and J. Weickert
   Is Dense Optical Flow Useful to Compute the Fundamental Matrix? - Updated Version with Errata.
   In Image Analysis and Recognition, Proc. 4th International Conference
   ICIAR 2008, Póvoa de Varzim, Portugal, June 2008 - A. Campilho, M. Kamel (Eds.)
   Lecture Notes in Computer Science, Vol. 5112, 630-639, Springer, Berlin, 2008.
   
   

Journal Papers



6. 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.
   


7. 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.
   
   

Technical Reports



8. C. Schmaltz, P. Peter, M. Mainberger, F. Ebel, J. Weickert, A. Bruhn:
   Understanding, Optimising, and Extending Data Compression with Anisotropic Diffusion.
   Technical Report No. 329, Department of Mathematics, Saarland University, Saarbrücken, Germany, March 2013.
   
   

Theses



9. M. Mainberger
   Contour Coding for PDE-based Image Reconstruction
   Master's Thesis in Visual Computing, Dept. of Computer Science,
   Saarland University, Saarbrücken, Germany, October 2008.
   
   
10. M. Mainberger
    Computing the fundamental matrix in computer vision from dense optic flow fields
    Bachelor's Thesis in Computer Science, Dept. of Computer Science,
    Saarland University, Saarbrücken, Germany, April 2007.
    
    

• Journal of Mathematical Imaging and Vision (JMIV)
• IEEE Transactions on Image Processing (IEEE-TIP)
• International Journal of Computer Vision (IJCV)
• Computer Vision and Image Understanding (CVIU)
• Transactions on Circuits and Systems for Video Technology (TCSVT)

• Winter term 2012/2013:
  Lecture Correspondence Problems in Computer Vision
  


• Summer term 2010:
  Tutorials to Differential Equations in Image Processing and Computer Vision
  Seminar Emerging Methods for Image Compression
  


• Winter term 2009/2010:
  Tutorials to Image Processing and Computer Vision


• Summer term 2009:
  Tutorials to Differential Equations in Image Processing and Computer Vision
  (Awarded by the mathematics students as best lecture in summer term 2009)


• Winter term 2008/2009:
  Tutorials to Image Processing and Computer Vision

1. Julian Steil
   B.Sc. Thesis in Computer Science (in progress)
2. Michael Puhl - Edge Based Image Compression with Mixed Boundary Conditions.
   B.Sc. Thesis in Computer Science (2012)
3. Nicolas Mach - Progressive Modi für Bildkomprimierungsverfahren, die partielle Differentialgleichungen nutzen.
   B.Sc. Thesis in Mathematics (2012)
4. Franziska Huth - Shape Coding with Quadrupoles.
   B.Sc. Thesis in Computer Science (2011)
5. Kevin Baum - Stützstellenauswahl für diffusionsbasierte Bildkompression unter Berücksichtigung einer Quadrixel-Substruktur-Restriktion.
   B.Sc. Thesis in Computer Science (2011)
6. Leonhard Keller - PDE-Based Image Reconstruction on the iPhone 4.
   B.Sc. Thesis in Mathematics(2011)
7. Rajiv Lund - 3-D Data Compression with Homogeneous Diffusion.
   M.Sc. Thesis in Computer Science(2011)
8. Sebastian Hoffmann - Grey-Value Optimisation in PDE-Based Image Compression.
   B.Sc. Thesis in Computer Science(2010)

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