A scalable algorithm for radio-interferometric imaging

Rafael E. Carrillo, Vijay Kartik, Jean-Philippe Thiran, Yves Wiaux

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In 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 paper, we propose a scalable algorithm for RI imaging that offers a highly parallelizable structure paving the way for next- generation high-dimensional data imaging. The proposed algorithm is based on a proximal linear version of the alternating direction method of multipliers (ADMM).
Original languageEnglish
Publication statusPublished - 2015
EventSignal Processing with Adaptive Sparse Structured Representations 2015 - Cambridge, United Kingdom
Duration: 6 Jul 20159 Jul 2015


ConferenceSignal Processing with Adaptive Sparse Structured Representations 2015
Abbreviated titleSPARS 2015
Country/TerritoryUnited Kingdom


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