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Proceedings Paper

Framed frames for data frames
Author(s): Nate Strawn
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Paper Abstract

We present a computationally efficient, data-driven procedure for constructing linear isometric embeddings of high-dimensional data (data frames) into spaces of smooth images, and thereby obtain tight frame dictionaries for the data space using tight frame dictionaries for the image space (“framed frames” – wavelets, curvelets, shearlets, etc.). Experiments indicate that data are more compressible in these induced dictionaries when compared to compressibility in terms of principal components.

Paper Details

Date Published: 24 August 2017
PDF: 7 pages
Proc. SPIE 10394, Wavelets and Sparsity XVII, 103941A (24 August 2017); doi: 10.1117/12.2274778
Show Author Affiliations
Nate Strawn, Georgetown Univ. (United States)


Published in SPIE Proceedings Vol. 10394:
Wavelets and Sparsity XVII
Yue M. Lu; Dimitri Van De Ville; Manos Papadakis, Editor(s)

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