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Proceedings Paper

Wavefront reconstruction in square region based on improved two-dimension Legendre polynomials
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Paper Abstract

In optical testing, such as the fringe reflection technology and Shack-Hartman wavefront sensor technology, slope of a surface is measured instead, from which the faithful surface of the test optic is obtained. Therefore, a gradient data-based wavefront reconstruction is needed. This paper shows the use of the Gram-Schmidt process for orthonormalizing the gradients of the two-dimensional Legendre polynomials. After a set of orthonormalized vector polynomials is generated in a square region, these polynomials can be used to fit the gradient data in the region. By a simple linear transformation, the fitting coefficients can be derived and transformed to the wavefront description of the two-dimension Legendre polynomials, and the wavefront and primary aberration are then obtained. Based on the zonal method, this can effectively reconstruct the high-frequency component by fitting the difference of the high-frequency error, which cannot be done by polynomial fitting. According to the computer simulation, this algorithm can primely realize the reconstruction of wavefront.

Paper Details

Date Published: 18 January 2019
PDF: 10 pages
Proc. SPIE 10839, 9th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test, Measurement Technology, and Equipment, 1083915 (18 January 2019); doi: 10.1117/12.2506234
Show Author Affiliations
Zhen Wu, Wuhan Univ. of Technology (China)
Key Lab. of Materials for High Power Laser (China)
Zhilin Xia, Wuhan Univ. of Technology (China)
Xuyu Li, Key Lab. of Materials for High Power Laser (China)
Qing Lu, Key Lab. of Materials for High Power Laser (China)
Chaoyang Wei, Key Lab. of Materials for High Power Laser (China)
Jianda Shao, Key Lab. of Materials for High Power Laser (China)


Published in SPIE Proceedings Vol. 10839:
9th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test, Measurement Technology, and Equipment
Fan Wu; Yudong Zhang; Xiaoliang Ma; Xiong Li; Bin Fan, Editor(s)

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