29 May 2013 Composite wavelet representations for reconstruction of missing data
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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.
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Wojciech Czaja, Julia Dobrosotskaya, Benjamin Manning, "Composite wavelet representations for reconstruction of missing data", Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 875003 (29 May 2013); doi: 10.1117/12.2019219; https://doi.org/10.1117/12.2019219
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