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Position: |
Former Research Assistant |
E-mail: |
hoffmann -at- mia.uni-saarland.de
(please replace anti-spam -at- by @)
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- PDE Based Image Compression
Conference Papers
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P. Peter, S. Hoffmann, F. Nedwed, L. Hoeltgen, J. Weickert:
From optimised inpainting with linear PDEs towards competitive image
compression codecs.
To appear in T. Bräunl, B. McCane, M. Rivers, X. Yu (Eds.):
Advances in Image and Video Technology.
Lecture Notes in Computer Science, Springer, Berlin, 2015.
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S. Hoffmann, G. Plonka, J. Weickert:
Discrete Green's functions for harmonic and biharmonic inpainting
with sparse atoms.
In X.-C. Tai, E. Bae, T. F. Chan, M. Lysaker (Eds.):
Energy Minimization Methods in Computer Vision and Pattern Recognition.
Lecture Notes in Computer Science, Springer, Vol. 8932, 169-182, Berlin,
2015.
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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.
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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, Proc. Third International Conference, Ein Gedi, Israel, May/June 2011.
Lecture Notes in Computer Science, Vol. 6667, 26-37, Springer, Berlin, 2012.
Technical Reports
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P. Peter, S. Hoffmann, F. Nedwed, L. Hoeltgen, J. Weickert:
Evaluating the True Potential of Diffusion-Based Inpainting in
a Compression Context.
Technical Report No. 373, Department of Mathematics,
Saarland University, Saarbrücken, Germany, January 2016.
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G. Plonka, S. Hoffmann, J. Weickert:
Pseudo-inverses of Difference Matrices and Their Application to
Sparse Signal Approximation.
arXiv:1504.04266 [math.NA], April 2015.
Book Chapters
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L. Hoeltgen, M. Mainberger, S. Hoffmann, J. Weickert, C. H. Tang,
S. Setzer, D. Johannsen, F. Neumann, B. Doerr:
Optimising spatial and tonal data for PDE-based inpainting.
To appear in M. Bergounioux, G. Peyré, C. Schnörr (Eds.):
Variational Methods in Image Analysis. De Gruyter, Berlin, 2016.
Also available as
arXiv:1506.04566 [cs.CV], June 2015.
Theses
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S. Hoffmann
Analysis of non-mass like tumors in breast MRI using methods of optical flow, segmentation and data mining
Master's Thesis in Visual Computing, Dept. of Computer Science,
Saarland University, Saarbrücken, Germany, December 2011.
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S. Hoffmann
Grey-value optimisation in PDE-based image compression
Bachelor's Thesis in Computer Science, Dept. of Computer Science,
Saarland University, Saarbrücken, Germany, August 2010.
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Jing Niu: A Steganography Inspired Application of Hiding a High Resolution Image in its Low Resolution Version.
M.Sc. Thesis in Computer Science 2015.
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Ayadi Chouikhi: Segmentation of Steel Microstructure Images using an Adapted Chan-Vese Approach.
Internship Thesis (Stage) in Computer Science (2014).
Joint Project with the Material Engineering Center Saarland (MECS).
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Markus Schneider: Image Compression with Homogeneous Diffusion Inpainting on Level Lines.
B.Sc. Thesis in Computer Science (2013).
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Michael Puhl: Edge Based Image Compression with Mixed Boundary Conditions.
B.Sc. Thesis in Computer Science (2012).
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