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Proceedings Paper

Compressed sensing in k-space: from magnetic resonance imaging and synthetic aperture radar
Author(s): Mike E. Davies; Chaoran Du; Shaun I. Kelly; Ian Marshall; Gabriel Rilling; Yuehui Tao
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Paper Abstract

We consider two imaging applications of compressed sensing where the acquired data corresponds to samples in the Fourier domain (aka k- space). The rst one is magnetic resonance imaging (MRI), which has been one of the standard examples in the compressed sensing literature. The second one is synthetic aperture radar (SAR). We consider the practical issues of applying compressed sensing ideas in these two applications noting that the physical prossesses involved in these two sensing modalities are very different. We consider the issues of: appropriate image models and sampling strategies, dealing with noise, and the need for calibration.

Paper Details

Date Published: 27 September 2011
PDF: 9 pages
Proc. SPIE 8138, Wavelets and Sparsity XIV, 81381G (27 September 2011); doi: 10.1117/12.893446
Show Author Affiliations
Mike E. Davies, The Univ. of Edinburgh (United Kingdom)
Chaoran Du, The Univ. of Edinburgh (United Kingdom)
Shaun I. Kelly, The Univ. of Edinburgh (United Kingdom)
Ian Marshall, The Univ. of Edinburgh (United Kingdom)
Gabriel Rilling, The Univ. of Edinburgh (United Kingdom)
Yuehui Tao, The Univ. of Edinburgh (United Kingdom)

Published in SPIE Proceedings Vol. 8138:
Wavelets and Sparsity XIV
Manos Papadakis; Dimitri Van De Ville; Vivek K. Goyal, Editor(s)

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