Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects
Gilboa G, Moeller M, Burger M (2016)
Publication Type: Journal article
Publication year: 2016
Journal
Publisher: Springer New York LLC
Book Volume: 56
Pages Range: 300-319
Issue: 2
DOI: 10.1007/s10851-016-0665-5
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.
Authors with CRIS profile
Involved external institutions
Technische Universität München (TUM)
Germany (DE)
Technion - Israel Institute of Technology
Israel (IL)
Westfälische Wilhelms-Universität (WWU) Münster
Germany (DE)
Germany (DE)
Technion - Israel Institute of Technology
Israel (IL)
Westfälische Wilhelms-Universität (WWU) Münster
Germany (DE)
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://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.
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