Sparse signal recovery in a transform domain
The ability to efficiently and sparsely represent seismic data is becoming an increasingly important problem in geophysics. Over the last thirty years many transforms such as wavelets, curvelets, contourlets, surfacelets, shearlets, and many other types of ‘x-lets’ have been developed. Such transfor...
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ndltd-UBC-oai-circle.library.ubc.ca-2429-41712018-01-05T17:23:13Z Sparse signal recovery in a transform domain Lebed, Evgeniy Wavelets Transforms Sparsity The ability to efficiently and sparsely represent seismic data is becoming an increasingly important problem in geophysics. Over the last thirty years many transforms such as wavelets, curvelets, contourlets, surfacelets, shearlets, and many other types of ‘x-lets’ have been developed. Such transform were leveraged to resolve this issue of sparse representations. In this work we compare the properties of four of these commonly used transforms, namely the shift-invariant wavelets, complex wavelets, curvelets and surfacelets. We also explore the performance of these transforms for the problem of recovering seismic wavefields from incomplete measurements. Science, Faculty of Mathematics, Department of Graduate 2009-02-04T15:42:17Z 2009-02-04T15:42:17Z 2008 2008-11 Text Thesis/Dissertation http://hdl.handle.net/2429/4171 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ 1390514 bytes application/pdf University of British Columbia |
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English |
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Others
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Wavelets Transforms Sparsity |
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Wavelets Transforms Sparsity Lebed, Evgeniy Sparse signal recovery in a transform domain |
description |
The ability to efficiently and sparsely represent seismic data is becoming an increasingly important problem in geophysics. Over the last thirty years many transforms such as wavelets, curvelets, contourlets, surfacelets, shearlets, and many other types of ‘x-lets’ have been developed. Such transform were leveraged to resolve this issue of sparse representations. In this work we compare the properties of four of these commonly used transforms, namely the shift-invariant wavelets, complex wavelets, curvelets and surfacelets. We also explore the performance of these transforms for the problem of recovering seismic wavefields from incomplete measurements. === Science, Faculty of === Mathematics, Department of === Graduate |
author |
Lebed, Evgeniy |
author_facet |
Lebed, Evgeniy |
author_sort |
Lebed, Evgeniy |
title |
Sparse signal recovery in a transform domain |
title_short |
Sparse signal recovery in a transform domain |
title_full |
Sparse signal recovery in a transform domain |
title_fullStr |
Sparse signal recovery in a transform domain |
title_full_unstemmed |
Sparse signal recovery in a transform domain |
title_sort |
sparse signal recovery in a transform domain |
publisher |
University of British Columbia |
publishDate |
2009 |
url |
http://hdl.handle.net/2429/4171 |
work_keys_str_mv |
AT lebedevgeniy sparsesignalrecoveryinatransformdomain |
_version_ |
1718581901797621760 |