Compressed sensing for infrared interferometric imaging

Interferometry is a high resolution technique that enables us to study physical processes at the smallest spatial scales that we can probe with our telescopes. In the infrared and in (sub-)millimetric Very-Long-Baseline Interferometry, the technique is restricted to sparse arrays with only a few telescopes or antennas. While imaging would the most intuitive way to interpret interferometric data, recovering images from sparse arrays is an ill-posed" problem and Fourier inversion techniques are restricted. In this work, we explore a novel imaging scheme based on Compressed Sensing to recover interferometric images. For this purpose, simulated data from the Aperture Masking mode of the James Webb Space Telescope are presented. Our results suggest that reliable interferometric images can be recovered using this technique. In particular, we highlights the recovery of the source structure with high-contrast and low-level residuals.