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Proceedings Paper

Image analysis algorithms for critically sampled curvature wavefront sensor images in the presence of large intrinsic aberrations
Author(s): Nirmal Bissonauth; Paul Clark; Gavin B. Dalton; Richard M. Myers; William J. Sutherland
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Paper Abstract

This paper describes the image analysis algorithm developed for VISTA to recover wavefront information from curvature wave front sensor images. This technique is particularly suitable in situations where the defocused images have a limited number of pixels and the intrinsic or null aberrations contribute significantly to distort the images. The algorithm implements the simplex method of Nelder and Mead. The simplex algorithm generates trial wavefront coefficients that are fed into a ray tracing algorithm which in turn produces a pair of defocused images. These trial defocused images are then compared against the images obtained from a sensor, using a fitness function. The value returned from the fitness function is fed back to the simplex algorithm, which then decides how the next set of trial coefficients is produced.

Paper Details

Date Published: 15 September 2004
PDF: 9 pages
Proc. SPIE 5496, Advanced Software, Control, and Communication Systems for Astronomy, (15 September 2004); doi: 10.1117/12.550063
Show Author Affiliations
Nirmal Bissonauth, Univ. of Durham (United Kingdom)
Paul Clark, Univ. of Durham (United Kingdom)
Gavin B. Dalton, Rutherford Appleton Lab. (United Kingdom)
Richard M. Myers, Univ. of Durham (United Kingdom)
William J. Sutherland, Univ. of Cambridge (United Kingdom)

Published in SPIE Proceedings Vol. 5496:
Advanced Software, Control, and Communication Systems for Astronomy
Hilton Lewis; Gianni Raffi, Editor(s)

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