紫外-可见双光谱成像系统的紫外图像滤波

陈涛; 李剑平; 邢胜; 董玉明; 焦国华

doi:10.3788/OPE.20172513.0325

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紫外-可见双光谱成像系统的紫外图像滤波

信息科学 | 更新时间：2020-08-13

- 紫外-可见双光谱成像系统的紫外图像滤波
- Filtering of UV images of UV-Vis dual-band imaging system
- 光学精密工程 2017年25卷第10s期页码：325-331
- 作者机构：
  
  1. 中国科学院深圳先进技术研究院,广东深圳,518055
  2. 中国科学院大学深圳先进技术研究院,广东深圳,518055
  3. 北京市供用电建设承发包有限公司北京,100062
- 作者简介：
- 基金信息：
  
  国家重点研发计划资助项目（No.2016YFB1200401）();深圳市科技创新技术攻关项目（No.JSGG20150602143353104）()
- DOI：10.3788/OPE.20172513.0325
  中图分类号： TP391.41
- 收稿日期：2017-06-28，
  
  修回日期：2017-07-11，
  
  纸质出版日期：2017-11-25
- 稿件说明：
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陈涛, 李剑平, 邢胜等. 紫外-可见双光谱成像系统的紫外图像滤波[J]. 光学精密工程, 2017,25(10s): 325-331

CHEN Tao, LI Jian-ping, XING Sheng etc. Filtering of UV images of UV-Vis dual-band imaging system[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 325-331
陈涛, 李剑平, 邢胜等. 紫外-可见双光谱成像系统的紫外图像滤波[J]. 光学精密工程, 2017,25(10s): 325-331 DOI： 10.3788/OPE.20172513.0325.

CHEN Tao, LI Jian-ping, XING Sheng etc. Filtering of UV images of UV-Vis dual-band imaging system[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 325-331 DOI： 10.3788/OPE.20172513.0325.

摘要

为了降低紫外-可见双光谱成像系统的可见图像与紫外图像配准过程中的图像噪声，提高图像配准精度，设计了基于相关运算的紫外图像滤波算法。首先，分析了紫外图像噪声的来源和特性，确定噪声的类型。然后，利用一个连续的掩模与紫外图像进行相关运算，通过设定合适的阈值来滤除噪声。最后，通过与几种滤波算法的滤波结果的比较来验证该算法的性能，并通过检测紫外图像中标定板的角点特征来进一步验证该滤波算法的效果。实验结果表明，与另外几种滤波方法相比，通过相关性滤波后的紫外图像的峰值信噪比（PSNR）最大，为45.31 dB，通过matlab编写滤波程序的运行时间为0.57 s。利用Shi-Tomasi算法能够检测出紫外图像中标定板的全部角点。因此，该滤波算法有较好的滤波效果，运算速度较快，对图像本身的信息损失小，能够满足高精度图像配准的要求。

Abstract

In order to reduce image noise and improve registration accuracy in visible and UV image registration of UV-Vis dual-band imaging system

a UV image filtering algorithm based on correlation operation was designed. Firstly

the type of noise was confirmed by analyzing sources and characteristics of UV image noise. Then

correlation operation was completed between UV image and a continuous mask

and the noise was eliminated through a suitable threshold. Finally

the algorithm was verified by comparing the result of correlation filtering and other filtering methods

and the effect of the correlation filtering algorithm was further verified by detecting the corner feature of calibration board in UV image. The experiments prove that the peak signal to noise ratio(PSNR) of filtered UV image is 45.31 dB by correlation filter

and it's running time is 0.57 s measured by matlab. Furthermore

the corner feature of calibration board in UV image was detected throughly by Shi-Tomasi algorithm. Therefore

the correlation filter can eliminate the noise of UV image with high-speed and less pixel loss

which can satisfy the requirement of high accuracy image registration.

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Keywords

references

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