Sparse interferometric Stokes imaging under polarization constraint (Polarized SARA)

Abstract

We develop a novel algorithm for sparse Stokes parameters imaging in radio interferometry under the polarization constraint. The latter is a physical non-linear relation between the Stokes parameters, imposing that the polarization intensity is a lower bound on the total intensity. To solve the joint inverse Stokes imaging problem including this bound, we leverage epigraphical projection techniques in convex optimization and design a primal-dual method offering a highly flexible and parallelizable structure. In addition, we propose to regularize each Stokes parameter map through an average sparsity prior in the context of a reweighted analysis approach (SARA). The resulting approach is dubbed Polarized SARA. We demonstrate on simulated observations of M87 with the Event Horizon Telescope that imposing the polarization constraint leads to superior image quality. The results also confirm that the performance of the average sparsity prior surpasses the alternative state-of-the-art priors for polarimetric imaging.

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Cited by in corpus (10)

• Image reconstruction algorithms in radio interferometry: from handcrafted to learned regularization denoisers
• Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA): I. Algorithm and simulations
• Polca SARA - Full polarization, direction-dependent calibration and sparse imaging for radio interferometry
• Super-resolution Imaging of the Protoplanetary Disk HD 142527 Using Sparse Modeling
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