Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Simon Setzer"'
Publikováno v:
Applied Mathematics & Optimization. 82:1017-1048
The principal component analysis (PCA) is a powerful standard tool for reducing the dimensionality of data. Unfortunately, it is sensitive to outliers so that various robust PCA variants were proposed in the literature. This paper addresses the robus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ae45539ddf5199dcdc33ca0e290e0a5
https://doi.org/10.1007/s00245-019-09566-1
https://doi.org/10.1007/s00245-019-09566-1
Autor:
Gabriele Steidl, Marzieh Hasannasab, Johannes Hertrich, Sebastian Neumayer, Gerlind Plonka, Simon Setzer
Publikováno v:
Journal of Fourier Analysis and Applications. 27
This article was originally published Online First without Open Access. After publication in volume 26, issue 4, the author decided to opt for Open Choice and to make the article an Open Access publication. Therefore, the copyright of the article has
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fd5429afe1e70587eb7a18de758f634
https://doi.org/10.1007/s00041-021-09848-9
https://doi.org/10.1007/s00041-021-09848-9
Autor:
Gabriele Steidl, Marzieh Hasannasab, Gerlind Plonka, Simon Setzer, Johannes Hertrich, Sebastian Neumayer
The aim of this paper is twofold. First, we show that a certain concatenation of a proximity operator with an affine operator is again a proximity operator on a suitable Hilbert space. Second, we use our findings to establish so-called proximal neura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b61ef13401a63d5d3c945ae8a2625c77
Principal component analysis (PCA) is a powerful tool for dimensionality reduction. Unfortunately, it is sensitive to outliers, so that various robust PCA variants were proposed in the literature. One of the most frequently applied methods for high d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c17bbfa21b9b98c40742a7c9add6fcf4
https://publica.fraunhofer.de/handle/publica/262714
https://publica.fraunhofer.de/handle/publica/262714
Publikováno v:
Image and Vision Computing. 57:114-129
We propose a novel variational approach to the depth-from-defocus problem. The quality of such methods strongly depends on the modelling of the image formation (forward operator) that connects depth with out-of-focus blur. Therefore, we discuss diffe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88424698b6c2a0143f40e680c9cda183
https://doi.org/10.1016/j.imavis.2016.08.011
https://doi.org/10.1016/j.imavis.2016.08.011
Publikováno v:
Computer Graphics Forum. 33:195-204
The problem of reconstructing a watertight surface from a finite set of oriented points has received much attention over the last decades. In this paper, we propose a general higher order framework for surface reconstruction. It is based on the idea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3503111e2f3073d450aecedc37f6a8ac
https://doi.org/10.1111/cgf.12445
https://doi.org/10.1111/cgf.12445
Publikováno v:
SIAM Journal on Imaging Sciences. 7:1588-1623
Alternating direction methods are a common tool for general mathematical programming and optimization. These methods have become particularly important in the field of variational image processing, which frequently requires the minimization of nondif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d196e6d827880ad463374d78b3c4ce52
https://doi.org/10.1137/120896219
https://doi.org/10.1137/120896219
Autor:
Laurent Hoeltgen, Markus Mainberger, Sebastian Hoffmann, Joachim Weickert, Ching Hoo Tang, Simon Setzer, Daniel Johannsen, Frank Neumann, Benjamin Doerr
Publikováno v:
Variational Methods ISBN: 9783110430394
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4eb79de51d693dec03d79230cb8a450
https://doi.org/10.1515/9783110430394-002
https://doi.org/10.1515/9783110430394-002
Publikováno v:
Computational Optimization and Applications. 54:417-440
In recent years, convex optimization methods were successfully applied for various image processing tasks and a large number of first-order methods were designed to minimize the corresponding functionals. Interestingly, it was shown recently in Grewe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83cf3740fcfa085e50294010eb436f69
https://doi.org/10.1007/s10589-012-9525-4
https://doi.org/10.1007/s10589-012-9525-4
Publikováno v:
Communications in Mathematical Sciences. 9:797-827
As first demonstrated by Chambolle and Lions the staircasing effect of the RudinOsher-Fatemi model can be reduced by using infimal convolutions of functionals containing higher order derivatives. In this paper, we examine a modification of such infim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec02a1da85238f9c351bbb9b0a8a8fe1
https://doi.org/10.4310/cms.2011.v9.n3.a7
https://doi.org/10.4310/cms.2011.v9.n3.a7