Bayesian image restoration for mosaic active imaging

Nicolas Lermé; François Malgouyres; Dominique Hamoir; Emmanuelle Thouin

doi:10.3934/ipi.2014.8.733

Article Contents

2014, Volume 8, Issue 3: 733-760. Doi: 10.3934/ipi.2014.8.733

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Bayesian image restoration for mosaic active imaging

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

Received: November 30, 2012

Revised: January 31, 2014

Published: July 2014

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Abstract

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.

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Mathematics Subject Classification: Primary: 68U10; Secondary: 94A08, 62M40, 90C27, 90C30.

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