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Introduction
Currently working as a Postdoctoral Research Assistant with research focus on partial differential equation based image compression and convex optimisation. See also http://www.mia.uni-saarland.de/hoeltgen/index.shtml for my old position at Saarland University and http://www-user.tu-cottbus.de/~hoeltgen/ for my current position in Cottbus
Additional affiliations
September 2018 - present

ITK Engineering
Position
- Engineer
April 2015 - present
October 2014 - March 2015
Education
September 2008 - August 2010
September 2005 - August 2008
Publications
Publications (36)
Ph.D. thesis in applied mathematics
Poster presentation from VIA 2011in Heidelberg, Germany
Finding optimal data for inpainting is a key problem for image-compression with partial differential equations. Not only the location of important pixels but also their values should be optimal to maximise the quality gain. The position of important data is usually encoded in a binary mask. Recent studies have shown that allowing non-binary masks m...
Finding optimal data for inpainting is a key problem in the context of partial differential equation-based image compression. We present a new model for optimising the data used for the reconstruction by the underlying homogeneous diffusion process. Our approach is based on an optimal control framework with a strictly convex cost functional contain...
Lossy image compression methods based on partial differential equations have received much attention in recent years. They may yield high-quality results but rely on the computationally expensive task of finding an optimal selection of data. For the possible extension to video compression, this data selection is a crucial issue. In this context, on...
Lossy image compression methods based on partial differential equations have received much attention in recent years. They may yield high quality results but rely on the computationally expensive task of finding optimal data.
Estimating shape and appearance of a three-dimensional object from a given set of images is a classic research topic that is still actively pursued. Among the various techniques available, photometric stereo is distinguished by the assumption that the underlying input images are taken from the same point of view but under different lighting conditi...
Laplace interpolation is a popular approach in image inpainting using partial differential equations. The classic approach considers the Laplace equation with mixed boundary conditions. Recently a more general formulation has been proposed where the differential operator consists of a point-wise convex combination of the Laplacian and the known ima...
Estimating shape and appearance of a three dimensional object from a given set of images is a classic research topic that is still actively pursued. Among the various techniques available, PS is distinguished by the assumption that the underlying input images are taken from the same point of view but under different lighting conditions. The most co...
A major task in non-rigid shape analysis is to retrieve correspondences between two almost isometric 3D objects. An important tool for this task are geometric feature descriptors. Ideally, a feature descriptor should be invariant under isometric transformations and robust to small elastic deformations. A successful class of feature descriptors empl...
Finding optimal data for inpainting is a key problem in the context of partial differential equation based image compression. The data that yields the most accurate reconstruction is real-valued. Thus, quantisation models are mandatory to allow an efficient encoding. These can also be understood as challenging data clustering problems. Although clu...
The aim of this paper is to deal with Poisson noise in images arising in electron microscopy. We consider here especially images featuring sharp edges and many relatively large smooth regions together with smaller strongly anisotropic structures. To deal with the denoising task, we propose a variational method combining a data fidelity term that ta...
Partial differential equations are well suited for dealing with image reconstruction tasks such as inpainting. One of the most successful mathematical frameworks for image reconstruction relies on variations of the Laplace equation with different boundary conditions. In this work we analyse these formulations and discuss the existence and uniquenes...
The main task in three dimensional shape matching is to retrieve correspondences between two similar three dimensional objects. To this end, a suitable point descriptor which is invariant under isometric transformations is required. A commonly used descriptor class relies on the spectral decomposition of the Laplace-Beltrami operator. Important exa...
Morphological levelings represent a useful tool for the decomposition of an image into cartoon and texture components. Moreover, they can be used to construct a morphological scale space. However, the classic construction of levelings is limited to the use of grey scale images, since an ordering of pixel values is required.
Partial differential equations have recently been used for image compression purposes. One of the most successful frameworks solves the Laplace equation using a weighting scheme to determine the importance of individual pixels. We provide a physical interpretation of this approach in terms of the Helmholtz equation which explains its superiority. F...
This paper presents a novel approach to distinguish driving styles with respect to their energy efficiency. A distinct property of our method is that it relies exclusively on Global Positioning System (GPS) logs of drivers. This setting is highly relevant in practice as these data can easily be acquired. Relying on positional data alone means that...
Estimating the shape and appearance of a three dimensional object from flat images is a challenging research topic that is still actively pursued. Among the various techniques available, Photometric Stereo (PS) is known to provide very accurate local shape recovery, in terms of surface normals. In this work, we propose to minimise non-convex variat...
We present a strategy for the recovery of a sparse solution of a common problem in acoustic engineering, which is the reconstruction of sound source levels and locations applying microphone array measurements. The considered task bears similarities to the basis pursuit formalism but also relies on additional model assumptions that are challenging f...
Partial differential equations (PDEs) are able to reconstruct images accurately from a small fraction of their image points. The inpainting capabilities of sophisticated anisotropic PDEs allow compression codecs with suboptimal data selection approaches to compete with transform-based methods like JPEG2000. For simple linear PDEs, optimal known dat...
Finding optimal data for inpainting is a key problem for image compression with partial differential equations (PDEs). Not only the location of important pixels but also their values should optimise the compression quality. The position of such important data is usually encoded in a binary mask. The corresponding pixel values are real valued and yi...
Poster corresponding to the conference paper with same name from Algoritmy 2016 Conference
Some recent methods for lossy signal and image compression store only a few selected pixels and fill in themissing structures by inpainting with a partial differential equation (PDE). Suitable operators include the Laplacian, the biharmonic operator, and edge-enhancing anisotropic diffusion (EED). The quality of such approaches depends substantiall...
For inpainting with linear partial differential equations (PDEs) such as homogeneous or biharmonic diffusion, sophisticated data optimisation strategies have been found recently. These allow high-quality reconstructions from sparse known data. While they have been explicitly developed with compression in mind, they have not entered actual codecs so...
Bregman iterations are known to yield excellent results for denoising,
deblurring and compressed sensing tasks, but so far this technique has rarely
been used for other image processing problems. In this paper we give a thorough
description of the Bregman iteration, unifying thereby results of different
authors within a common framework. Then we sh...
Bachelor thesis in mathematics (in German)
Some recent methods for lossy signal and image compression store only a few selected pixels and fill in the missing structures by inpainting with a partial differential equation (PDE). Suitable operators include the Laplacian, the biharmonic operator, and edge-enhancing anisotropic diffusion (EED). The quality of such approaches depends substantial...
The Euler-Lagrange framework and splitting based methods are among the most popular approaches to solve variational optic
flow problems. These methods are commonly embedded in a coarse-to-fine strategy to be able to handle large displacements.
While the use of a denoising filter inbetween the warping is an important tool for splitting based approac...