Centroids computation and point spread function analysis for reverse Hartmann test

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• 作者：Zhu Zhao ; Mei Hui ; ^{huim@bit.edu.cn} ; Ming Liu ; Liquan Dong ; Lingqin Kong ; Yuejin Zhao
• 关键词：Point spread function ; Circle of confusion ; Centroid algorithm ; Gaussian and super-Gaussian approximations ; Reverse Hartmann test
• 刊名：Optics Communications
• 出版年：2017
• 出版时间：15 March 2017
• 年：2017
• 卷：387
• 期：Complete
• 页码：328-337
• 全文大小：1577 K
• 卷排序：387

文摘

In reverse Hartmann test, intensity distribution of PSF is classified as circle of confusion (CoC) and evaluated in terms of Lommel function. The features of CoC are discussed and simulated. Fitting of a spot with Gaussian or super-Gaussian profile to identify its centroid forms the basis of the centroids algorithm. When correlation coefficient is >0.999, the CoC the can be approximated with a Gaussian profile like the Airy disk. To improve the precision, it can be fitted by super-Gaussian with appropriate order. On noised image, the centroid computed by super-Gaussian fitting has a less shift and it grows at a slower pace, so that the super-Gaussian fitting method has the better anti-noise capability in centroid computation. Segmental fringe is served as a ‘spot’ with an infinite diameter in one direction. The centroids computation for segmental fringe with 2D and 1D Gaussian or super-Gaussian fitting has 10−5 order of magnitude, which further confirm the feasibility and advantage of our method.