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).
|Publication status||Published - 2015|
|Event||Signal Processing with Adaptive Sparse Structured Representations 2015 - Cambridge, United Kingdom|
Duration: 6 Jul 2015 → 9 Jul 2015
|Conference||Signal Processing with Adaptive Sparse Structured Representations 2015|
|Abbreviated title||SPARS 2015|
|Period||6/07/15 → 9/07/15|
Carrillo, R. E., Kartik, V., Thiran, J-P., & Wiaux, Y. (2015). A scalable algorithm for radio-interferometric imaging. Paper presented at Signal Processing with Adaptive Sparse Structured Representations 2015, Cambridge, United Kingdom.