Thomas Richter

Stefan Frei, Thomas Richter, Thomas Wick

In this work, we describe a simple finite element approach that is able to resolve weak discontinuities in interface problems accurately. The approach is based on a fixed patch mesh consisting of quadrilaterals, that will stay unchanged independent of the position of the interface. Inside the patches we refine once more, either in eight triangles or in four quadrilaterals, in such a way that the interface is locally resolved. The resulting finite element approach can be considered a fitted finite element approach. In our practical implementation, we do not construct this fitted mesh, however. Instead, the local degrees of freedom are included in a parametric way in the finite element space, or to be more precise in the local mappings between a reference patch and the physical patches. We describe the implementation in the open source C++ finite element library deal.II in detail and present two numerical examples to illustrate the performance of the approach. Finally, detailed studies of the behavior of iterative linear solvers complement this work.

Johan Hoffman, Bärbel Holm, Thomas Richter

We present a locally adapted parametric finite element method for interface problems. For this adapted finite element method we show optimal convergence for elliptic interface problems with a discontinuous diffusion parameter. The method is based on the adaption of macro elements where a local basis represents the interface. The macro elements are independent of the interface and can be cut by the interface. A macro element which is a triangle in the triangulation is divided into four subtriangles. On these subtriangles, the basis functions of the macro element are interpreted as linear functions. The position of the vertices of these subtriangles is determined by the location of the interface in the case a macro element is cut by the interface. Quadrature is performed on the subtriangles via transformations to a reference element. Due to the locality of the method, its use is well suited on distributed architectures.

Srivatsa Prativadibhayankaram, Mahadev Prasad Panda, Thomas Richter et al.

We propose the structure and color based learned image codec (SLIC) in which the task of compression is split into that of luminance and chrominance. The deep learning model is built with a novel multi-scale architecture for Y and UV channels in the encoder, where the features from various stages are combined to obtain the latent representation. An autoregressive context model is employed for backward adaptation and a hyperprior block for forward adaptation. Various experiments are carried out to study and analyze the performance of the proposed model, and to compare it with other image codecs. We also illustrate the advantages of our method through the visualization of channel impulse responses, latent channels and various ablation studies. The model achieves Bjøntegaard delta bitrate gains of 7.5% and 4.66% in terms of MS-SSIM and CIEDE2000 metrics with respect to other state-of-the-art reference codecs.