Scalable Algorithm for Polarization Constrained Sparse Interferometric Stokes Imaging

Jasleen Birdi, Audrey Repetti, Yves Wiaux

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
26 Downloads (Pure)

Abstract

Polarized emissions from various astrophysical sources provide an additional means to infer the properties of the source. This information can be extracted by imaging the Stokes parameters characterizing these emissions, from the incomplete Fourier sampling measurements provided by the radio interferometer. To solve the corresponding ill-posed inverse problem, we recently proposed the Polarized SARA method which exploits the polarization constraint along with imposing an average sparsity prior for each of the Stokes parameters, encompassed in a reweighting approach. Motivated by the large amounts of data produced by the next-generation radio interferometers, in the current work, we propose a scalable version of this method, combined with an accelerating strategy. We showcase the performance of this improved method on a real dataset acquired by the Very Large Array (VLA).
Original languageEnglish
Title of host publication2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM)
PublisherIEEE
Pages465-469
Number of pages5
ISBN (Electronic)9781538647523
DOIs
Publication statusPublished - 30 Aug 2018

Publication series

NameSensor Array and Multichannel Signal Processing Workshop (SAM)
PublisherIEEE
ISSN (Electronic)2151-870X

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  • Cite this

    Birdi, J., Repetti, A., & Wiaux, Y. (2018). Scalable Algorithm for Polarization Constrained Sparse Interferometric Stokes Imaging. In 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM) (pp. 465-469). (Sensor Array and Multichannel Signal Processing Workshop (SAM)). IEEE. https://doi.org/10.1109/SAM.2018.8448968