Apparaît dans la collection : Variational methods and optimization in imaging

In this work, we are interested in the resolution of inverse problems raised in many image processing applications. We considered inverse problems starting from models (understanding the acquisition process), then addressing their resolution (formulated as an optimization problem) while considering the parameters or hyperparameters involved all along the process (e.g. noise nature/intensity, regularization parameters). Different models will be considered corresponding to different application cases such as tensor factorization, source separation or time-frequency inpainting. All these issues have been addressed by adopting a variational approach leading to various optimization problems that we propose to solve by developing proximal approaches.