Acta Optica Sinica, Volume. 43, Issue 6, 0612006(2023)
Sharpness Evaluation Algorithm Based on Real-Time Automatic Focusing of 1.2 m Telescope System
Fig. 1. Definition of FWHM
Fig. 2. HFD of different type of images. (a) Noise image; (b) faint star; (c) star in focus
Fig. 3. Algorithm flow chart
Fig. 4. Comparison of images before and after anisotropic diffusion method processing. (a) Original image; (b) image after processing
Fig. 5. Comparison of images before and after Qtsu algorithm processing. (a) Original image; (b) image after processing
Fig. 6. Comparison of images before and after cluster algorithm processing. (a) Original image; (b) image after processing
Fig. 7. Performance comparison of algorithms. (a) Performance comparison of algorithms under different noise when FWHM is constant; (b) performance comparison of algorithms under different spot sizes when SNR is constant
Fig. 8. Partial image sequences of object 33320
Fig. 9. Outlier detection
Fig. 10. FWHM values obtained by fitting for different frames of image numbered 33320 (arrow points to direction of increase of i)
Fig. 11. Focusing curve fitted with measured FWHM
Fig. 12. HFD of different image frames in target numbered 33320
Fig. 13. V-shaped focusing curves after fitting
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Mengxue Yang, Zhulian Li, Rongwang Li, Yuqiang Li. Sharpness Evaluation Algorithm Based on Real-Time Automatic Focusing of 1.2 m Telescope System[J]. Acta Optica Sinica, 2023, 43(6): 0612006
Category: Instrumentation, Measurement and Metrology
Received: May. 13, 2022
Accepted: Aug. 10, 2022
Published Online: Mar. 13, 2023
The Author Email: Li Yuqiang (lyq@ynao.ac.cn)