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Full Record Details
Persistent URL
http://purl.org/net/epubs/work/10790816
Record Status
Checked
Record Id
10790816
Title
Image analysis algorithms for critically sampled curvature wavefront sensor images in the presence of large intrinsic aberrations
Contributors
N Bissonauth (Durham U.)
,
P Clark (Durham U.)
,
R Myers (Durham U.)
,
G Dalton (CCLRC Rutherford Appleton Lab.)
,
W Sutherland (Cambridge U.)
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 Neider 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.
Organisation
CCLRC
,
SSTD
,
SSTD-IS
Keywords
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Language
English (EN)
Type
Details
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Year
Journal Article
Proceedings of SPIE - The International Society for Optical Engineering 5496 (2004): 738-746. Is in proceedings of: Advanced Software, Control, and Communication Systems for Astronomy, Glasgow, 21 Jun 2004.
doi:10.1117/12.550063
2004
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