基于邻域向量内积局部对比度图像增强的光学元件损伤检测

王拯洲; 段亚轩; 王力; 谭萌; 李红光; 魏际同

doi:10.3788/OPE.20192712.2668

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基于邻域向量内积局部对比度图像增强的光学元件损伤检测

信息科学 | 更新时间：2020-07-09

- 基于邻域向量内积局部对比度图像增强的光学元件损伤检测
- Detecting optical component damage based on neighborhood vector dot contrast image enhancement
- 光学精密工程 2019年27卷第12期页码：2668-2682
- 作者机构：
  
  中国科学院西安光学精密机械研究所，陕西西安 710119
- 作者简介：
  
  [ "王拯洲(1976-)，男，陕西旬邑人，博士，高级工程师，硕士生导师，2007年于西北工业大学获得硕士学位，2017年于西安交通大学获得博士学位，主要从事图像分类与目标检测和激光参数测量的研究。E-mail：azhou_china@126.com" ]
  段亚轩(1983-)，男，陕西宝鸡人，博士，高级工程师，硕士生导师，2008年于南京理工大学获得硕士学位，2019年于中国科学院大学获得博士学位，主要从事光学精密测量与仪器方面的研究。E-mail：duanyaxuan@opt.ac.cn
- 基金信息：
  
  国家自然科学基金资助项目(61705254);国家自然科学基金资助项目(U1930118)
- DOI：10.3788/OPE.20192712.2668
  中图分类号： TP391.1
- 收稿日期：2019-08-13，
  
  录用日期：2019-8-29，
  
  纸质出版日期：2019-12-25
- 稿件说明：
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王拯洲, 段亚轩, 王力, 等. 基于邻域向量内积局部对比度图像增强的光学元件损伤检测[J]. 光学精密工程, 2019,27(12):2668-2682.

Zheng-zhou WANG, Ya-xuan DUAN, Li WANG, et al. Detecting optical component damage based on neighborhood vector dot contrast image enhancement[J]. Optics and precision engineering, 2019, 27(12): 2668-2682.
王拯洲, 段亚轩, 王力, 等. 基于邻域向量内积局部对比度图像增强的光学元件损伤检测[J]. 光学精密工程, 2019,27(12):2668-2682. DOI： 10.3788/OPE.20192712.2668.

Zheng-zhou WANG, Ya-xuan DUAN, Li WANG, et al. Detecting optical component damage based on neighborhood vector dot contrast image enhancement[J]. Optics and precision engineering, 2019, 27(12): 2668-2682. DOI： 10.3788/OPE.20192712.2668.

摘要

为了解决局域对比度方法(LCM)无法检测局部亮区损伤目标和分离效率低的问题，本文提出了基于邻域向量内积局部对比度图像增强的光学元件损伤目标检测方法。首先，将图像中的每一个点的3×3邻域生成一个9维邻域向量，并将邻域内的最大值扩展成一个9维度极值向量，计算邻域向量与极值向量的内积；其次，计算每个像素的邻域向量内积对比度值(NVDC)；然后，计算每个像素的邻域向量内积局部对比度，即在一个较大的区域内(5×5)搜索当前像素所有邻域向量内积对比度的最大值，作为当前像素的邻域向量内积局部对比度值(NVDLC)；最后，对NVDLC图像进行二值化和目标分离。实验结果表明，通过本文的增强方法使得损伤图像的信噪比从3.775提高到12.445，损伤目标信号得到极大的增强。在经过邻域向量内积局部对比度方法图像增强后，能够直接使用自适应阈值公式将小于2 pixel的损伤目标从背景中分离出来，满足了弱对比度损伤目标检测对于精度和效率的要求。

Abstract

To solve the problems of the inability of LCM in detecting damaged targets in local bright areas and its low separation efficiency

a damage detection method based on local contrast image enhancement of a neighborhood vector local dot was proposed in this study. First

a nine-dimensional neighborhood vector was generated from the 3×3 neighborhood of each point in the image

and the maximum value in the neighborhood was extended to the nine-dimensional extreme vector in calculating the dots of the neighborhood vector and extreme vector. Second

the Neighborhood Vector Dot Contrast (NVDC) of each pixel was calculated. Third

the NVDC of the image patch of each pixel was calculated

i.e.

the maximum NVDC value of each pixel in a relatively large area(5×5) was taken as the final Neighborhood Vector Dot Local Contrast (NVDLC) of the corresponding pixel. Fourth

the NVDLC image was binarized

and the targets were separated from the background. The experimental results demonstrate that the LSNR of the damaged image is improved from 3.775 to 12.445

and the signal of the damage target is significantly enhanced using the image enhancement method proposed in this study. After the maximum contrast image of NVDLC is enhanced

the damage targets with size of less than 2 pixels can be directly separated from the background using the adaptive threshold formula

which meets the accuracy and efficiency requirements of the weak contrast damage target detection.

关键词

Keywords

references

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