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math.NA2026

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…

math.NA2026

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…

math.NA2025

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…

math.NA2024

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…

math.NA2024

Denoising Hyperbolic-Valued Data by Relaxed Regularizations

Robert Beinert, Jonas Bresch

We introduce a novel relaxation strategy for denoising hyperbolic-valued data. The main challenge is here the non-convexity of the hyperbolic sheet. Instead of considering the deno…

math.NA2024

Denoising of Sphere- and SO(3)-Valued Data by Relaxed Tikhonov Regularization

Robert Beinert, Jonas Bresch, Gabriele Steidl

Manifold-valued signal- and image processing has received attention due to modern image acquisition techniques. Recently, a convex relaxation of the otherwise nonconvex Tikhonov-re…