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.

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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.

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