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Proceedings Paper

Composite wavelet representations for reconstruction of missing data
Author(s): Wojciech Czaja; Julia Dobrosotskaya; Benjamin Manning
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Paper Abstract

We shall introduce a novel methodology for data reconstruction and recovery, based on composite wavelet representations. These representations include shearlets and crystallographic wavelets, among others, and they allow for an increased directional sensitivity in comparison with the standard multiscale techniques. Our new approach allows us to recover missing data, due to sparsity of composite wavelet representations, especially when compared to inpainting algorithms induced by traditional wavelet representations, and also due to the flexibility of our variational approach.

Paper Details

Date Published: 29 May 2013
PDF: 14 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 875003 (29 May 2013); doi: 10.1117/12.2019219
Show Author Affiliations
Wojciech Czaja, Univ. of Maryland, College Park (United States)
Julia Dobrosotskaya, Univ. of Maryland, College Park (United States)
Benjamin Manning, Univ. of Maryland, College Park (United States)


Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)

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