7 papers
A Discrete Radon Transform Based on the Area of Cube-Plane Intersection
Robert Beinert, Jonas Bresch, Michael Quellmalz
The Radon transform is a fundamental tool for analyzing data in tomographic imaging, optimal transport, crystallography, and geometric analysis. Numerical computations require an a…
Generalizations of the Normalized Radon Cumulative Distribution Transform for Limited Data Recognition
Matthias Beckmann, Robert Beinert, Jonas Bresch
The Radon cumulative distribution transform (R-CDT) exploits one-dimensional Wasserstein transport and the Radon transform to represent prominent features in images. It is closely…
Unsupervised Ground Metric Learning
Janis Auffenberg, Jonas Bresch, Oleh Melnyk +1
Data classification without access to labeled samples remains a challenging problem. It usually depends on an appropriately chosen distance between features, a topic addressed in m…
Denoising Multi-Color QR Codes and Stiefel-Valued Data by Relaxed Regularizations
Robert Beinert, Jonas Bresch
The handling of manifold-valued data, for instance, plays a central role in color restoration tasks relying on circle- or sphere-valued color models, in the study of rotational or…
Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
Matthias Beckmann, Robert Beinert, Jonas Bresch
The Radon cumulative distribution transform (R-CDT), is an easy-to-compute feature extractor that facilitates image classification tasks especially in the small data regime. It is…
Max-Normalized Radon Cumulative Distribution Transform for Limited Data Classification
Matthias Beckmann, Robert Beinert, Jonas Bresch
The Radon cumulative distribution transform (R-CDT) exploits one-dimensional Wasserstein transport and the Radon transform to represent prominent features in images. It is closely…