对比度(视觉)
荧光
像素
激光器
分割
材料科学
光学
人工智能
计算机视觉
计算机科学
物理
作者
Qinxiao Liu,Rui Dong,Hongjie Liu,Fang Wang,Ye Tian,Hu D,Chaoyuan Ding
摘要
In large high-power laser devices,the surface and subsurface defects of fused silica optical components directly affect the laser damage threshold and imaging quality. In this paper, fluorescence imaging technology is used to obtain images of defects in the subsurface layer of optical components that will absorb laser. Because the original image has the characteristics of sparse signal, weak intensity, low contrast, etc. In order to efficiently and reliably evaluate the surface and subsurface defects, this paper proposes a weak and small defect detection method based on local adaptive contrast enhancement and seed region growth. Firstly, the local adaptive contrast enhancement method is used to enhance the contrast of the original image. Secondly, the method of bilateral filtering is used to denoise. Thirdly, seed region growth method is used to segment the defective regions and perform morphological processing. Finally, defect detection is performed. The experiment uses different segmentation methods to detect images in different regions. The results show that this method can significantly enhance the contrast of the original fluorescence image, and detect pixel-level defects, and the detection rate is stable at about 95%. Meanwhile, the reasons, size distribution and other characteristics of the sub-surface defects of fused silica optical components are analyzed. This paper provides a nondestructive method of detecting weak and small defects in the subsurface layer of the optical element faster and higher accuracy.
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