Chinese Journal of Liquid Crystals and Displays, Volume. 40, Issue 7, 1036(2025)
Wavefront detection method based on extended Nijboer-Zernike combined with deep neural networks
Fig. 5. Point spread function(PSF)intensity distribution at the defocused and in-focus positions
Fig. 6. (a)Comparison results between the NN-OIOFS,GS algorithm and the ENZ-RS Net method;(b)Results of the average original wavefront root mean square(RMS)and residual wavefront root mean square error(RMSE).
Fig. 7. (a)Real part of
Fig. 8. (a)Incident wavefront;(b,c)Reconstructed wavefront and residual wavefront by ENZ-RS Net model;(d,e)Reconstructed wavefront and residual wavefront by GS algorithm;(f,g)Reconstructed wavefront and residual wavefront by NN-OIOFS model. NA=0.3.
Fig. 9. (a)Incident wavefront;(b,c)Reconstructed wavefront and residual wavefront by ENZ-RS Net model;(d,e)Reconstructed wavefront and residual wavefront by GS algorithm;(f,g)Reconstructed wavefront and residual wavefront by NN-OIOFS model. NA=0.9.
Fig. 10. (a)Real part of
Fig. 11. (a)Comparison results between the GS algorithm and the ENZ-RS Net method;(b)Results of the average original wavefront root mean square(RMS)and residual wavefront root mean square error(RMSE).
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Jinting LI, Bin WANG, Lei DONG, Shuo LI. Wavefront detection method based on extended Nijboer-Zernike combined with deep neural networks[J]. Chinese Journal of Liquid Crystals and Displays, 2025, 40(7): 1036
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Received: Mar. 20, 2025
Accepted: --
Published Online: Aug. 11, 2025
The Author Email: Bin WANG (eatingbeen@hotmail.com)