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通过平面图像校准改进计算机生成的莫尔轮廓术。

Improved computer-generated moiré profilometry with flat image calibration.

作者信息

Wang Lu, Cao Yiping, Li Chengmeng, Wan Yingying, Li Hongmei, Xu Cai, Zhang Hechen

出版信息

Appl Opt. 2021 Feb 10;60(5):1209-1216. doi: 10.1364/AO.412291.

Abstract

An improved computer-generated moiré profilometry (CGMP) with flat image calibration is proposed. In CGMP, the purification of the AC component plays a decisive role. While a composite grating modulated with both the sinusoidal grating and its background light substitutes for the sinusoidal grating itself, the sinusoidal deformed pattern and flat image can be demodulated from the captured pattern. It is found that the sinusoidal deformed pattern and flat image may deviate, which is caused by ambient light. So flat image calibration is conducted to obtain a purer AC component that can effectively suppress the influence of ambient light and ensure the measurement accuracy, even if spectrum aliasing exists. Experimental results show the feasibility and validity of the proposed method.

摘要

提出了一种改进的具有平面图像校准的计算机生成莫尔轮廓术(CGMP)。在CGMP中,交流分量的提纯起着决定性作用。当用正弦光栅及其背景光调制的复合光栅替代正弦光栅本身时,可以从捕获的图案中解调正弦变形图案和平坦图像。发现正弦变形图案和平坦图像可能会出现偏差,这是由环境光引起的。因此,进行平面图像校准以获得更纯净的交流分量,即使存在频谱混叠,该交流分量也能有效抑制环境光的影响并确保测量精度。实验结果表明了该方法的可行性和有效性。

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