I lead the Lab for Mathematical Methods in Computer Vision and Machine Learning at Technische Hochschule Würzburg-Schweinfurt (THWS). The lab maintains the following open-source toolkits for variational methods for signal and image processing:
| Repository | What it does | Languages | Install |
|---|---|---|---|
| Pottslab | Multilabel image segmentation via the Potts / piecewise-constant Mumford-Shah model | Java, MATLAB, Python | pip install pottslab |
| L1TV | Exact L1-TV regularisation of real- or circle-valued signals | MATLAB, Rust, Python | pip install l1tv |
| CSSD | Cubic smoothing splines for signals with discontinuities | MATLAB, Rust, Python | pip install cssd |
| MumfordShah2D | Edge-preserving image restoration via the Mumford-Shah model | MATLAB, Java, Rust, Python | pip install mumfordshah2d |
| CircleMedianFilter | Fast median filtering for phase or orientation data | MATLAB, C++, Python | pip install pycirclemedianfilter |
| DCEBE | Bolus arrival time estimation for DCE-MRI signals | MATLAB, Python | pip install dcebe |
Every repository ships a CITATION.cff — use GitHub's "Cite this repository" button to get BibTeX or APA in one click.
| Repository | What it does | Co-author |
|---|---|---|
| HOMS_SignalProcessing | Higher-order Mumford-Shah models for joint smoothing and partitioning of 1D signals and time series | Lukas Kiefer |
| PALMS_ImagePartitioning | Piecewise affine-linear Mumford-Shah for image partitioning (online demo) | Lukas Kiefer |
| pcw-regrs | Degrees-of-freedom penalised piecewise regression | Stefan Volz |