A time-regularized blind deconvolution method via non-convex optimisationMS72

Radio-astronomical imaging aims to probe a sky intensity image through an antenna array. The reconstruction quality highly depends on the calibration accuracy of the radio telescope. In this context, unknown time-dependent calibration kernels appearing in the measurement equation must be estimated. We rely on an alternating forward-backward structure to jointly estimate the sky image and the kernels, by solving a non-convex minimization problem incorporating data fidelity and advanced regularization terms.

This presentation is part of Minisymposium “MS72 - Inverse problems with imperfect forward models (2 parts)
organized by: Yury Korolev (University of Cambridge) , Martin Burger (University of Muenster) .

Audrey Repetti (Heriot-Watt University, Edinburgh)
Pierre-Antoine Thouvenin (Institut National Polytechnique de Toulouse)
Arwa Dabbech (Heriot-Watt University)
Yves Wiaux (Heriot-Watt University)
image deblurring, image reconstruction, inverse problems