基于多光谱图像融合的光学表面疵病检测
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西安工业大学 光电工程学院 西安 710021

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TH741

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Optical surface defect detection based on multispectral image fusion
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School of Optelectronic Engineering, Xi’ an Technological University, Xi’an 710021,China

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    摘要:

    为了实现对精密光学元件表面疵病的高精度测量,提出了一种基于多光谱图像融合的光学元件表面疵病检测方法。通过使用不同波长的光源入射到光学表面,在显微暗场成像系统中获得了450nm,532nm,650nm单波长光源照明时光学表面疵病的检测结果,并将采集到的图片通过加权平均法、拉普拉斯金字塔变换法和小波变换法三种方法进行图像融合后,再进行图像处理获取疵病尺寸信息。由实验结果对比可知,相较于单波长原始图像的疵病检测结果,多光谱融合图像的检测结果更加精确,并且通过对比三种融合方法结果,其中以拉普拉斯金字塔变换融合的效果最佳。

    Abstract:

    In order to achieve high-precision measurement of surface defects of precision optical elements, a surface defect detection method of optical elements based on multispectral image fusion is proposed. By using light sources of different wavelengths incident on the optical surface, the detection results of optical surface defects illuminated by single wavelength light sources of 450nm, 532nm and 650nm are obtained in the micro dark field imaging system. After the collected images are fused by three methods: weighted average method, Laplace pyramid transform method and wavelet transform method, then image processing is performed to obtain the defect size information. By comparing the experimental results, compared with the defect detection results of single wavelength original image, the detection results of multispectral fusion image are more accurate, and by comparing the results of three fusion methods, the Laplace pyramid transform fusion has the best effect.

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向江华,刘缠牢.基于多光谱图像融合的光学表面疵病检测[J].电子测量技术,2022,45(3):131-135

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  • 在线发布日期: 2024-06-14
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