Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Rafael E Carrillo, Jason D McEwen, Yves Wiaux

Research output: Contribution to conferencePaper

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Abstract

n recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this talk, I will review our latest contributions in RI imaging, which leverage the versatility of convex optimization to both handle realistic continuous visibilities and offer a highly parallelizable structure paving the way to high-dimensional data scalability. Firstly, I will review our recently proposed average sparsity approach, SARA, which relies on the observation that natural images exhibit strong average sparsity over multiple coherent bases. Secondly, I will discuss efficient implementations of SARA, and sparse regularization problems in general, for large-scale imaging problems in a new toolbox dubbed PURIFY.
Original languageEnglish
Number of pages1
Publication statusPublished - 2015
EventBASP Frontiers 2015 - Villars-sur-Ollon, Lausanne, Switzerland
Duration: 25 Jan 201530 Jan 2015

Workshop

WorkshopBASP Frontiers 2015
CountrySwitzerland
CityLausanne
Period25/01/1530/01/15

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  • Cite this

    Carrillo, R. E., McEwen, J. D., & Wiaux, Y. (2015). Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging. Paper presented at BASP Frontiers 2015, Lausanne, Switzerland.