2016/10/31 by Luke Pratley, Jason D. McEwen, Mayeul d’Avezac +4 · 63 citations
Engineering · Physics and Astronomy · #Algorithm #Artificial intelligence #Astronomical interferometer #Compressed sensing #Computer science #Computer vision #Database #Image (mathematics) #Interferometry #Interpolation (computer graphics) #Iterative reconstruction #Kernel (algebra) #Optics #Physics #Radio Astronomy Observations and Technology #Scalability #Sparse and Compressive Sensing Techniques #Synthetic Aperture Radar (SAR) Applications and Techniques #astro-ph.IM
paper · pdf · doi:10.1093/mnras/stx2237
published in Monthly Notices of the Royal Astronomical Society 473(1), 1038-1058 (Oxford University Press) · 22 pages, 10 figures, PURIFY code available at http://basp-group.github.io/purify
openalex publication_date 2017/09/07 · arxiv created 2017/11/17 · arxiv updated 2017/11/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Next-generation radio interferometers, such as the Square Kilometre Array, will revolutionize our understanding of the Universe through their unprecedented sensitivity and resolution. However, to realize these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as clean, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the purify software package. In particular, we implement and apply the proximal alternating direction method of multipliers algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions while providing a computational saving and an analytic form. Secondly, we apply purify to real interferometric observations from the Very Large Array and the Australia Telescope Compact Array and find that images recovered by purify are of higher quality than those recovered by clean. Thirdly, we discuss how purify reconstructions exhibit additional advantages over those recovered by clean. The latest version of purify, with developments presented in this work, is made publicly available.