skip to content

Researchers: Ferdia Sherry, Erlend Riis, Luca Calatroni

A key issue in image denoising, and in inverse problems as a whole, is the correct choice of data priors and fidelity terms. Depending on this choice, different results are obtained. Several strategies, both physical - dictated by the physics behind the acquisition process - and statistically grounded (e.g. by estimating or learning noise and structure in the data), have been considered in the literature. We consider approaches that learn the model and the parameter choice by bilevel optimisation techniques.