1 October 1994 Image-spectrum signal-to-noise-ratio improvements by statistical frame selection for adaptive-optics imaging through atmospheric turbulence
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Optical Engineering, 33(10), (1994). doi:10.1117/12.181250
Abstract
Adaptive-optics systems have been used to overcome some of the effects of atmospheric turbulence on large-aperture astronomical telescopes. However, the correction provided by adaptive optics cannot restore diffraction-limited performance, due to discretized spatial sampling of the wavefront, limited degrees of freedom in the adaptive-optics system, and wavefront sensor measurement noise. Field experience with adaptive-optics imaging systems making short-exposure image measurements has shown that some of the images are better than others in the sense that the better images have higher resolution. This is a natural consequence of the statistical nature of the compensated optical transfer function in an adaptive-optics telescope. Hybrid imaging techniques have been proposed that combine adaptive optics and postdetection image processing to improve the high-spatial-frequency information of images. Performance analyses of hybrid methods have been based on prior knowledge of the ensemble statistics of the underlying random process. Improved image-spectrum SNRs have been predicted, and in some cases experimentally demonstrated. In this paper we address the issue of selecting and processing the best images from a finite data set of compensated short-exposure images. Image sharpness measures are used to select the data subset to be processed. Comparison of the image-spectrum SNRs for the cases of processing the entire data set and processing only the selected subset of the data shows a broad range of practical cases where processing the selected subset results in superior SNR.
Michael C. Roggemann, Craig A. Stoudt, Byron M. Welsh, "Image-spectrum signal-to-noise-ratio improvements by statistical frame selection for adaptive-optics imaging through atmospheric turbulence," Optical Engineering 33(10), (1 October 1994). https://doi.org/10.1117/12.181250
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