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Proceedings Paper

Regularized multiframe myopic deconvolution from wavefront sensing
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Paper Abstract

Deconvolution from wavefront sensing is a powerful and low cost high resolution imaging technique designed to compensate for the image degradation due to atmospheric turbulence. It is based on a simultaneous recording of shift exposure images and wavefront sensor (WFS) data. To date, the data processing consists of a sequential estimation of the wavefronts given the WFS data and then of the object given the reconstructed wavefronts and the images. Thus, the information about the wavefronts present in the images if not used for the wavefront estimation. The aim of this communication is to propose and validate a novel method called myopic deconvolution from wavefront sensing. It is a joint estimation of the object of interest and the unknown wavefronts using all data simultaneously in a coherent Bayesian framework. It takes into account the noise in the images and in the wavefront sensor measurements, and the available a priori information on the object to be restored as well as on the wavefronts. As to the object a priori information, an edge-preserving prior is implemented and validated. This method is validated on simulations and on experimental astronomical data.

Paper Details

Date Published: 5 October 1999
PDF: 11 pages
Proc. SPIE 3763, Propagation and Imaging through the Atmosphere III, (5 October 1999); doi: 10.1117/12.363607
Show Author Affiliations
Laurent M. Mugnier, Office National d'Etudes et de Recherches Aerospatiales (France)
Clelia Robert, Office National d'Etudes et de Recherches Aerospatiales (France)
Jean-Marc Conan, Office National d'Etudes et de Recherches Aerospatiales (France)
Vincent Michau, Office National d'Etudes et de Recherches Aerospatiales (France)
S. Salem, Office National d'Etudes et de Recherches Aerospatiales (France)


Published in SPIE Proceedings Vol. 3763:
Propagation and Imaging through the Atmosphere III
Michael C. Roggemann; Luc R. Bissonnette, Editor(s)

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