American Institute of Mathematical Sciences

August  2014, 8(3): 733-760. doi: 10.3934/ipi.2014.8.733

Bayesian image restoration for mosaic active imaging

 1 LTCI, CNRS UMR5141, Institut Mines-Télécom, Télécom ParisTech, Paris, France 2 IMT, CNRS UMR5219, Université de Toulouse, Toulouse, France 3 ONERA - The French Aerospace Lab, F-31055 Toulouse, France, France

Received  December 2012 Revised  February 2014 Published  August 2014

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 (TV), and deduce a restoration algorithm. This algorithm is a two-stage iterative process which alternates between: i) the estimation of the restored image; ii) 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.
Citation: Nicolas Lermé, François Malgouyres, Dominique Hamoir, Emmanuelle Thouin. Bayesian image restoration for mosaic active imaging. Inverse Problems & Imaging, 2014, 8 (3) : 733-760. doi: 10.3934/ipi.2014.8.733
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