297 citations · 1.5k across the 199 of their papers we have counts for
8 papers · 1 filter
Variational image regularization with Euler's elastica using a discrete gradient scheme
Torbjørn Ringholm, Jasmina Lazić, Carola-Bibiane Schönlieb
This paper concerns an optimization algorithm for unconstrained non-convex problems where the objective function has sparse connections between the unknowns. The algorithm is based…
Choose your path wisely: gradient descent in a Bregman distance framework
Martin Benning, Marta M. Betcke, Matthias J. Ehrhardt +1
We propose an extension of a special form of gradient descent -- in the literature known as linearised Bregman iteration -- to a larger class of non-convex functions. We replace th…
An Anisotropic Interaction Model for Simulating Fingerprints
Bertram Düring, Carsten Gottschlich, Stephan Huckemann +2
Evidence suggests that both the interaction of so-called Merkel cells and the epidermal stress distribution play an important role in the formation of fingerprint patterns during p…
Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation
Leon Bungert, David A. Coomes, Matthias J. Ehrhardt +3
Hyperspectral imaging is a cutting-edge type of remote sensing used for mapping vegetation properties, rock minerals and other materials. A major drawback of hyperspectral imaging…
Numerical analysis of shell-based geometric image inpainting algorithms and their semi-implicit extension
L. Robert Hocking, Thomas Holding, Carola-Bibiane Schoenlieb
In this paper we study a class of fast geometric image inpainting methods based on the idea of filling the inpainting domain in successive shells from its boundary inwards. Image p…
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications
Antonin Chambolle, Matthias J. Ehrhardt, Peter Richtárik +1
We propose a stochastic extension of the primal-dual hybrid gradient algorithm studied by Chambolle and Pock in 2011 to solve saddle point problems that are separable in the dual v…
Learning Filter Functions in Regularisers by Minimising Quotients
Martin Benning, Guy Gilboa, Joana Sarah Grah +1
Learning approaches have recently become very popular in the field of inverse problems. A large variety of methods has been established in recent years, ranging from bi-level learn…
Nonlinear Spectral Image Fusion
Martin Benning, Michael Möller, Raz Z. Nossek +4
In this paper we demonstrate that the framework of nonlinear spectral decompositions based on total variation (TV) regularization is very well suited for image fusion as well as mo…