Application and Development of Wavefront Sensor Technology

Zhao, Suyang; Cheng, Xuemin

doi:10.11648/j.ijmsa.20170603.17

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…Carmen Canovas and Erez N. Ribak compared and analyzed SHWFS methods (convolution, interpolation, Fourier methods, and centroid methods) for ophthalmology, and found that the Fourier method has the best effect for pupils with a small slope of the boundary or with a large distance from the boundary [ 19 ]. In the field of optical detection, such as the surface shape detection of high-order parabolic mirrors and conventional optical elements, it is important to reduce the measurement error by overcoming the problem of steep or linear edges [ 20 , 21 , 22 , 23 , 24 ]. In addition, researchers are focused on trying to rectify the distortion caused by the atmosphere to the propagating laser beam, which may detect optical vortices [ 25 , 26 , 27 , 28 ].…”

Section: Introductionmentioning

confidence: 99%

A Method Used to Improve the Dynamic Range of Shack–Hartmann Wavefront Sensor in Presence of Large Aberration

Yang

Wang

2022

Sensors

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With the successful application of the Shack–Hartmann wavefront sensor in measuring aberrations of the human eye, researchers found that, when the aberration is large, the local wavefront distortion is large, and it causes the spot corresponding to the sub-aperture of the microlens to shift out of the corresponding range of the sub-aperture. However, the traditional wavefront reconstruction algorithm searches for the spot within the corresponding range of the sub-aperture of the microlens and reconstructs the wavefront according to the calculated centroid, which leads to wavefront reconstruction errors. To solve the problem of the small dynamic range of the Shack–Hartmann wavefront sensor, this paper proposes a wavefront reconstruction algorithm based on the autocorrelation method and a neural network. The autocorrelation centroid extraction method was used to calculate the centroid in the entire spot map in order to obtain a centroid map and to reconstruct the wavefront by matching the centroid with the microlens array through the neural network. This method breaks the limitation of the sub-aperture of the microlens. The experimental results show that the algorithm improves the dynamic range of the first 15 terms of the Zernike aberration reconstruction to varying degrees, ranging from 62.86% to 183.87%.

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