Abstract

The limitation of mechanical structure and misoperations can result in a small tilt angle formed by the sample and the focal plane, which will decrease the resolution of the imaging system. Moreover, the small tilt angle is difficult to be observed. In order to solve this problem, a monitoring algorithm of tilt angle based on sub-block plane fitting for high-resolution imaging systems has been proposed, which is used to measure the initial angle of most 2D samples before imaging and assist users to determine the tilt degree of the sample. Experiments demonstrate that the proposed method can measure the tilt angle with a high measurement precision of 0.007° and a low residual tilt angle of 0.004°, indicating that the algorithm has high measurement precision and stability. Further results show that the quality of the image will be improved by 20%–27% when the tilt angle is 0.3056°, which means that the small degree of tilt of the sample can seriously damage the image quality. Therefore, the study of tilt angle measurement has great significance for high-resolution imaging systems.

© 2019 Optical Society of America

High-precision algorithms for critical angle refractive index measurement

Yun Luo, Wenping Guo, Long Yu, Min Xia, Wei Li, and Kecheng Yang
Appl. Opt. 58(22) 6057-6062 (2019)

Tilted wavefront coding system to eliminate the retroreflection with superior imaging property

Lei Wang, Qing Ye, Jinsong Nie, and Xiaoquan Sun
Appl. Opt. 58(26) 7205-7211 (2019)

Optical section imaging of the tilted planes by illumination-angle-scanning digital interference holography

Yunseong Jeon and Chung Ki Hong
Appl. Opt. 49(27) 5110-5116 (2010)

Sub-pixel position estimation algorithm based on Gaussian fitting and sampling theorem interpolation for wafer alignment

Songyong Pan, Shaoqing Wang, Jinghao Xu, Lili Fan, Fenghua Yuan, Ting Shu, Fengzhao Dai, Xiaona Yan, Yang Bu, and Xiangzhao Wang
Appl. Opt. 60(31) 9607-9618 (2021)

Precision optical path alignment system for point diffraction interferometer based on image information

Zhuo Zhao, Bing Li, Xiaoqin Kang, Lei Chen, and Xiang Wei
Appl. Opt. 58(14) 3703-3711 (2019)