Compressed sensing image reconstruction for the LOFAR Radio Telescope

Hugh Garsden; Jean-Luc Starck; Stéphane Corbel; Cyril Tasse; Arnaud Woiselle

doi:10.1117/12.2027588

26 September 2013 Compressed sensing image reconstruction for the LOFAR Radio Telescope

Hugh Garsden, Jean-Luc Starck, Stéphane Corbel, Cyril Tasse, Arnaud Woiselle

Proceedings Volume 8858, Wavelets and Sparsity XV; 88581E (2013) https://doi.org/10.1117/12.2027588
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

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.

Citation Download Citation

Hugh Garsden, Jean-Luc Starck, Stéphane Corbel, Cyril Tasse, and Arnaud Woiselle "Compressed sensing image reconstruction for the LOFAR Radio Telescope", Proc. SPIE 8858, Wavelets and Sparsity XV, 88581E (26 September 2013); https://doi.org/10.1117/12.2027588

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