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Laurent Hoeltgen
Laurent Hoeltgen
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Zitiert von
Jahr
An optimal control approach to find sparse data for Laplace interpolation
L Hoeltgen, S Setzer, J Weickert
Energy Minimization Methods in Computer Vision and Pattern Recognition: 9th …, 2013
592013
Evaluating the true potential of diffusion-based inpainting in a compression context
P Peter, S Hoffmann, F Nedwed, L Hoeltgen, J Weickert
Signal Processing: Image Communication 46, 40-53, 2016
302016
Optimising spatial and tonal data for PDE-based inpainting
L Hoeltgen, M Mainberger, S Hoffmann, J Weickert, CH Tang, S Setzer, ...
Variational Methods, 35-83, 2017
282017
Why does non-binary mask optimisation work for diffusion-based image compression?
L Hoeltgen, J Weickert
Energy Minimization Methods in Computer Vision and Pattern Recognition: 10th …, 2015
172015
From optimised inpainting with linear PDEs towards competitive image compression codecs
P Peter, S Hoffmann, F Nedwed, L Hoeltgen, J Weickert
Image and Video Technology: 7th Pacific-Rim Symposium, PSIVT 2015, Auckland …, 2016
162016
Theoretical foundation of the weighted laplace inpainting problem
L Hoeltgen, A Kleefeld, I Harris, M Breuß
Applications of mathematics 64, 281-300, 2019
92019
Clustering-based quantisation for PDE-based image compression
L Hoeltgen, P Peter, M Breuß
Signal, Image and Video Processing 12, 411-419, 2018
92018
Optimised photometric stereo via non-convex variational minimisation
L Hoeltgen, Y Quéau, M Breuß, G Radow
British Machine Vision Association (BMVA), 2016
82016
Shape matching by time integration of partial differential equations
R Dachsel, M Breuß, L Hoeltgen
Scale Space and Variational Methods in Computer Vision: 6th International …, 2017
62017
Sparse regularisation of matrix valued models for acoustic source characterisation
L Hoeltgen, M Breuß, G Herold, E Sarradj
Optimization and Engineering 19, 39-70, 2018
52018
Optimisation of classic photometric stereo by non-convex variational minimisation
G Radow, L Hoeltgen, Y Quéau, M Breuß
Journal of Mathematical Imaging and Vision 61, 84-105, 2019
42019
The classic wave equation can do shape correspondence
R Dachsel, M Breuß, L Hoeltgen
Computer Analysis of Images and Patterns: 17th International Conference …, 2017
42017
Matrix-valued levelings for colour images
M Breuß, L Hoeltgen, A Kleefeld
Mathematical Morphology and Its Applications to Signal and Image Processing …, 2017
42017
Optimal interpolation data for image reconstructions
LA Hoeltgen
42014
Towards PDE-based video compression with optimal masks prolongated by optic flow
M Breuß, L Hoeltgen, G Radow
Journal of Mathematical Imaging and Vision 63, 144-156, 2021
32021
A Study of Spectral Expansion for Shape Correspondence
R Dachsel, M Breuß, L Hoeltgen
Proceedings of OAGM Workshop, 73-79, 2018
22018
Understanding image inpainting with the help of the Helmholtz equation
L Hoeltgen
Mathematical Sciences 11 (1), 73-77, 2017
22017
Analytic existence and uniqueness results for PDE-based image reconstruction with the Laplacian
L Hoeltgen, I Harris, M Breuß, A Kleefeld
Scale Space and Variational Methods in Computer Vision: 6th International …, 2017
22017
Bregman iteration for correspondence problems: A study of optical flow
L Hoeltgen, M Breuß
arXiv preprint arXiv:1510.01130, 2015
22015
Intermediate flow field filtering in energy based optic flow computations
L Hoeltgen, S Setzer, M Breuß
Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th …, 2011
22011
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