Frame selection performance limits for statistical image reconstruction of adaptive optics compensated images

Details Frame selection performance limits for statistical image reconstruction of adaptive optics compensated images Frame selection performance limits for statistical image reconstruction of adaptive optics compensated images

Aug 1995

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995spie.2534..235f&link_type=abstract

Proc. SPIE Vol. 2534, p. 235-246, Adaptive Optical Systems and Applications, Robert K. Tyson; Robert Q. Fugate; Eds.

Statistics

Applications

Scientific paper

Adaptive optics systems have been used to compensate for the degrading effects of atmospheric turbulence in images collected with large astronomical telescopes. Post-detection processing techniques are also employed to further improve adaptive optics compensated images. Typically, many short exposure images are collected, recentered to compensate for tilt, and then averaged to overcome randomness in the images and improve signal-to-noise ratio (SNR). Experience shows that some short exposure images in a data set are better than others. The frame selection post-detection processing technique uses an image quality metric to discard low quality frames and improve image spectrum SNR. In this paper, we address key issues pertaining to frame selection performance limits. Theoretical noise tradeoffs are used to establish minimum object brightness for successful application of the frame selection technique. Limits imposed by noise effects result in a minimum object brightness of apparent visual magnitude +8 for point sources and +4 for a typical satellite model imaged with a 1 m diameter telescope with no central obscuration. Effective average point spread functions for point source and extended objects after frame selection processing under equivalent seeing conditions are almost identical. Thus, deconvolution could be applied to images obtained via frame selection.

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