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Harmonic and Applied Analysis pp 199–248Cite as

Birkhäuser

Optimally Sparse Data Representations

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Part of the book series: Applied and Numerical Harmonic Analysis ((ANHA,volume 68))

Abstract

This chapter is dedicated to the question of how to efficiently encode a given class of signals. We introduce several mathematical techniques to construct optimal data representations for a number of signal types. Specifically we study the optimal approximation of functions governed by anisotropic singularities such as edges in images.

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Author information

Authors and Affiliations

  1. Seminar for Applied Mathematics, ETH Zürich, Rämistrasse 101, 8092, Zurich, Switzerland

    Philipp Grohs

Authors
  1. Philipp Grohs
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Correspondence to Philipp Grohs .

Editor information

Editors and Affiliations

  1. Mathematics and Computer Sciences, Philipps-Universität Marburg, Marburg, Hessen, Germany

    Stephan Dahlke

  2. Department of Mathematics, Università di Genova, Genova, Italy

    Filippo De Mari

  3. Applied Mathematics, ETH Zürich, Zürich, Zürich, Switzerland

    Philipp Grohs

  4. Department of Mathematics, University of Houston, Houston, Texas, USA

    Demetrio Labate

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Grohs, P. (2015). Optimally Sparse Data Representations. In: Dahlke, S., De Mari, F., Grohs, P., Labate, D. (eds) Harmonic and Applied Analysis. Applied and Numerical Harmonic Analysis, vol 68. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-18863-8_5

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