Wavelet Sparse Regularization for Manifold-Valued Data
Numerical Analysis
2018-08-03 v1 Computer Vision and Pattern Recognition
Numerical Analysis
Differential Geometry
Abstract
In this paper, we consider the sparse regularization of manifold-valued data with respect to an interpolatory wavelet/multiscale transform. We propose and study variational models for this task and provide results on their well-posedness. We present algorithms for a numerical realization of these models in the manifold setup. Further, we provide experimental results to show the potential of the proposed schemes for applications.
Cite
@article{arxiv.1808.00505,
title = {Wavelet Sparse Regularization for Manifold-Valued Data},
author = {Martin Storath and Andreas Weinmann},
journal= {arXiv preprint arXiv:1808.00505},
year = {2018}
}