Bayesian image restoration for mosaic active imaging

Nicolas Lermé (1) , François Malgouyres (2) , Dominique Hamoir (3) , Emmanuelle Thouin (3)

1 LISITE - Laboratoire d'Informatique, Signal et Image, Electronique et Télécommunication
2 IMT - Institut de Mathématiques de Toulouse UMR5219
3 ONERA - The French Aerospace Lab [Châtillon]

In this paper, we focus on the restoration of images acquired with a new active imaging concept. This new instrument generates a mosaic of active imaging acquisitions. We first describe a simplified forward model of this so-called ''mosaic active imaging''. We also assume a prior on the distribution of images, using the \ac{TV}, and deduce a restoration algorithm. This algorithm iterates one step for the estimation of the restored image and one step for the estimation of the acquisition parameters. We then provide the details useful to the implementation of these two steps. In particular, we show that the image estimation can be performed with graph-cuts. This allows a fast resolution of this image estimation step. Finally, we detail numerical experiments showing that acquisitions made with a mosaic active imaging device can be restored even under severe noise levels, with few acquisitions.

Mots clés: graph-cut; active imaging; laser imaging; image reconstruction; image estimation

Domaines: Optimisation et contrôle [math.OC]; Optique [physics.optics]

Nicolas Lermé, François Malgouyres, Dominique Hamoir, Emmanuelle Thouin. Bayesian image restoration for mosaic active imaging. Inverse Problems and Imaging , 2014, 8 (3), pp.733-760. ⟨hal-00758753v3⟩