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Proceedings Paper

Compressed sensing image reconstruction for the LOFAR Radio Telescope
Author(s): Hugh Garsden; Jean-Luc Starck; Stéphane Corbel; Cyril Tasse; Arnaud Woiselle
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Paper Abstract

The LOFAR Radio Telescope is a radio interferometer with multiple antennas placed throughout Europe. A radio interferometer samples the image of the sky in the Fourier domain; recovering the image from these samples is an inverse problem. In radio astronomy the CLEAN method has been used for many years to find a solution. Recent papers have established a link between radio interferometry and compressed sensing, which supports sparse recovery methods to reconstruct an image from interferometric data. The goal of this paper is to study sparse recovery methods on LOFAR data by comparing the accuracy of CLEAN and compressed sensing when applied to simulated LOFAR observations.

Paper Details

Date Published: 26 September 2013
PDF: 7 pages
Proc. SPIE 8858, Wavelets and Sparsity XV, 88581E (26 September 2013); doi: 10.1117/12.2027588
Show Author Affiliations
Hugh Garsden, Commissariat à l'Énergie Atomique, CNRS, Univ. Paris Diderot (France)
Jean-Luc Starck, Commissariat à l'Énergie Atomique, CNRS, Univ. Paris Diderot (France)
Stéphane Corbel, Commissariat à l'Énergie Atomique, CNRS, Univ. Paris Diderot (France)
Cyril Tasse, SKA South Africa (South Africa)
GEPI, Observatoire de Paris, CNRS, Univ. Paris Diderot (France)
Arnaud Woiselle, Commissariat à l'Énergie Atomique, CNRS, Univ. Paris Diderot (France)
Sagem SA (France)


Published in SPIE Proceedings Vol. 8858:
Wavelets and Sparsity XV
Dimitri Van De Ville; Vivek K. Goyal; Manos Papadakis, Editor(s)

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