Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects

Journal article


Publication Details

Author(s): Gilboa G, Moeller M, Burger M
Journal: Journal of Mathematical Imaging and Vision
Publisher: Springer New York LLC
Publication year: 2016
Volume: 56
Pages range: 300-319
ISSN: 0924-9907


Abstract

We present in this paper the motivation and theory of nonlinear spectral representations, based on convex regularizing functionals. Some comparisons and analogies are drawn to the fields of signal processing, harmonic analysis, and sparse representations. The basic approach, main results, and initial applications are shown. A discussion of open problems and future directions concludes this work.


External institutions with authors

Technion - Israel Institute of Technology
Technische Universität München (TUM)
Westfälische Wilhelms-Universität (WWU) Münster


How to cite

APA:
Gilboa, G., Moeller, M., & Burger, M. (2016). Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects. Journal of Mathematical Imaging and Vision, 56, 300-319. https://dx.doi.org/10.1007/s10851-016-0665-5

MLA:
Gilboa, Guy, Michael Moeller, and Martin Burger. "Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects." Journal of Mathematical Imaging and Vision 56 (2016): 300-319.

BibTeX: 

Last updated on 2018-03-12 at 09:23