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Persistent URL http://purl.org/net/epubs/work/10790816
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Record Id 10790816
Title Image analysis algorithms for critically sampled curvature wavefront sensor images in the presence of large intrinsic aberrations
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
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Language English (EN)
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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