KEYWORDS: Wavefronts, Digital signal processing, Adaptive optics, Field programmable gate arrays, Computing systems, Control systems, Deformable mirrors, Detection and tracking algorithms, Computer programming, Image processing
This paper summarizes the design methods of adaptive optical systems based on different types of platforms in recent years, classifies them according to the types of platforms they use (five categories in total), summarizes the design methods, performance indicators and achievements of each system, and reviews the feasible directions of some methods for subsequent optimization. Different adaptive optical systems need to be designed according to their goals, and the selection of computing platforms and the design of algorithms need to be considered comprehensively.
Spot location algorithms greatly influence the wavefront measurement error of the Shack–Hartmann wavefront sensor. Based on numerical simulations and experiments, we compare the wavefront reconstruction error of several spot location algorithms under different signal-to-noise ratio (SNR) conditions. We solve the problem of how to select the most suitable spot location algorithm and optimal parameters under different SNR conditions, which mimic the realistic working environment of the adaptive optics system changes. We find the optimal threshold and optimal window setting rules of the center of gravity (COG), intensity weighted centroiding, and weighted center of gravity (WCOG) algorithms. The correctness of our recommendation of spot location algorithms under different SNR conditions is supported by numerical simulations and experiments. We find that when the SNR is extremely low, that is the SNR is lower than 2, the cross-correlation algorithm and the thresholding WCOG algorithm are the best choices. When the SNR is moderately low, that is the SNR ranges from 2 to 10, the best choice is the thresholding WCOG algorithm. When the SNR is high, that is, the SNR is higher than 10, the simple algorithm of thresholding COG is the best choice.
The centroid method is commonly adopted to locate the spot in the sub-apertures in the Shack-Hartmann wavefront sensor (SH-WFS), in which preprocessing image is required before calculating the spot location due to that the centroid method is extremely sensitive to noises. In this paper, the SH-WFS image was simulated according to the characteristics of the noises, background and intensity distribution. The Optimal parameters of SH-WFS image preprocessing method were put forward, in different signal-to-noise ratio (SNR) conditions, where the wavefront reconstruction error was considered as the evaluation index. Two methods of image preprocessing, thresholding method and windowing combing with thresholding method, were compared by studying the applicable range of SNR and analyzing the stability of the two methods, respectively.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.