Statistics – Computation
Scientific paper
Sep 1998
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1998spie.3353..160t&link_type=abstract
Proc. SPIE Vol. 3353, p. 160-171, Adaptive Optical System Technologies, Domenico Bonaccini; Robert K. Tyson; Eds.
Statistics
Computation
4
Scientific paper
We present preliminary results from a comparison of image estimation and recovery algorithms developed for use with advanced telescope instrumentation and adaptive optics systems. Our study will quantitatively compare the potential of these techniques to boost the resolution of imagery obtained with undersampled or low-bandwidth adaptive optics; example applications are optical observations with IR- optimized AO, AO observations in server turbulence, and AO observations with dim guidestars. We will compare the algorithms in terms of morphological and relative radiometric accuracy as well as computational efficiency. Here, we present qualitative comments on image results for two levels each of seeing, object brightness, and AO compensation/wavefront sensing.
Ford Stephen D.
Hunt Bobby R.
Paxman Richard G.
Roggemann Michael C.
Rountree Janet C.
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