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Proceedings Paper

Deconvolution from wavefront sensing with optimal wavefront estimation techniques
Author(s): Scott R. Maethner; Michael C. Roggemann; Byron M. Welsh
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Paper Abstract

Minimum variance wave front estimation techniques are used to improve Deconvolution from Wave front Sensing (DWFS), a method to mitigate the effects of atmospheric turbulence on imaging systems. Both least-squares and minimum variance wave front phase estimation techniques are investigated, using both Gaussian and Zernike polynomial elementary functions. Imaging simulations and established performance metrics are used to evaluate these wave front estimation techniques for a one-meter optical telescope. Results show that the minimum variance estimation technique that employs Zernike polynomial elementary functions provides the best mean and signal-to-noise ratio performance of all the investigated wave front estimation techniques.

Paper Details

Date Published: 23 September 1997
PDF: 10 pages
Proc. SPIE 3125, Propagation and Imaging through the Atmosphere, (23 September 1997); doi: 10.1117/12.279024
Show Author Affiliations
Scott R. Maethner, U.S. Air Force (United States)
Michael C. Roggemann, Air Force Institute of Technology (United States)
Byron M. Welsh, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 3125:
Propagation and Imaging through the Atmosphere
Luc R. Bissonnette; Christopher Dainty, Editor(s)

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