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Proceedings Paper

Prediction of the space-varying point spread function for reconstruction of anisoplanatic adaptive optics images
Author(s): Mathieu Aubailly; Michael C. Roggemann; Timothy J. Schulz
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Paper Abstract

Atmospheric turbulence corrupts astronomical images formed by ground-based telescopes. Adaptive optics (AO) systems allow the effects of turbulence-induced aberrations to be reduced for a narrow field of view (FOV) corresponding approximately to the isoplanatic angle θ0. For field angles larger than θ0, the point spread function (PSF) gradually degrades as the field angle increases. In this paper, we present a technique to predict the PSF as function of the field angle. The predicted PSF is compared to the simulated PSF and the mean square (MS) error between the predicted and the simulated PSF never exceeds 2.7%. Simulated anisoplanatic intensity images of a star field are reconstructed by mean of a block-processing method using the predicted PSF. Two methods for image recovery are used: the Tikhonov regularization and the expectation maximization (EM) algorithm. The deconvolution results using the space-varying predicted PSF are compared to deconvolution results using the space-invariant on-axis PSF. The reconstruction technique using the predicted PSF shows an improvement of the MS error between the reconstructed image and the object of 7.2% to 84.8% compared to the on-axis PSF reconstruction.

Paper Details

Date Published: 25 August 2005
PDF: 12 pages
Proc. SPIE 5903, Astronomical Adaptive Optics Systems and Applications II, 590308 (25 August 2005); doi: 10.1117/12.639428
Show Author Affiliations
Mathieu Aubailly, Michigan Technological Univ. (United States)
Michael C. Roggemann, Michigan Technological Univ. (United States)
Timothy J. Schulz, Michigan Technological Univ. (United States)

Published in SPIE Proceedings Vol. 5903:
Astronomical Adaptive Optics Systems and Applications II
Robert K. Tyson; Michael Lloyd-Hart, Editor(s)

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