Detection probability of infrared and visible image fusion system

XU Hui; ZHANG Jun-ju; YUAN Yi-hui; ZHANG Peng-hui; HAN Bo

doi:10.3788/OPE.20132112.3205

您当前的位置：

首页 >

文章列表页 >

Detection probability of infrared and visible image fusion system

更新时间：2020-08-12

- Detection probability of infrared and visible image fusion system
- Optics and Precision Engineering Vol. 21, Issue 12, Pages: 3205-3213(2013)
- 作者机构：
  
  南京理工大学电子工程与光电技术学院
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20132112.3205
  CLC： TN215;TP391
- Received：01 February 2013，
  
  Revised：13 May 2013，
  
  Published Online：25 December 2013，
  
  Published：25 December 2013
- 稿件说明：
移动端阅览
许辉张俊举袁轶慧张鹏辉韩博. 红外与可见光图像融合系统的探测概率[J]. 光学精密工程, 2013,21(12): 3205-3213

XU Hui ZHANG Jun-ju YUAN Yi-hui ZHANG Peng-hui HAN Bo. Detection probability of infrared and visible image fusion system[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3205-3213
许辉张俊举袁轶慧张鹏辉韩博. 红外与可见光图像融合系统的探测概率[J]. 光学精密工程, 2013,21(12): 3205-3213 DOI： 10.3788/OPE.20132112.3205.

XU Hui ZHANG Jun-ju YUAN Yi-hui ZHANG Peng-hui HAN Bo. Detection probability of infrared and visible image fusion system[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3205-3213 DOI： 10.3788/OPE.20132112.3205.

摘要

提出了一种定量计算红外与可见光图像融合系统目标探测概率的方法，建立了该融合系统的目标探测概率计算模型。首先，研究了影响目标探测概率的主要因素:目标与背景的光谱对比度、红外与可见光探测器的特性、环境照度条件、融合图像质量、目标大小与距离。针对这些影响因素，分别构建了5个影响目标探测概率因素的数学模型。在此基础上，设计了基于红外与可见光图像融合系统的探测概率计算模型。最后，针对两组实际任务进行了实验。以第一组为例，其对于单一探测系统目标为树木的探测概率pvis为0.294 8，pIR为0.136 0，而采用不同算法的融合系统探测概率为0.414 2，远高于单一探测器的探测概率。得到的结果验证了融合系统的目标探测概率计算方法的有效性，证明了融合图像质量以及目标自身的光谱特性对融合系统目标探测概率起着重要作用。该模型实验结果符合人眼视觉特征。

Abstract

A method to calculate the target detection probability quantitatively for a infrared and visible image fusion system was proposed and a corresponding calculation model was established. First

the main factors affecting on the target detection probability were analyzed

and they were the spectral contrast of target and background

the characteristics of infrared and visible light detector

environmental illumination conditions

the integration of image quality

and the target size and distance. Then

five mathematical models on the effect factors mentioned above was constructed. On this basis

a calculation model for the detection probability based on infrared and visible image fusion system was completed. Finally

the experiments for two practical missions were performed. The first experiment show its results as follows: target detection probability of trees for a single detection system pvis is 0.294 8

pIR is 0.136 0

but the detection probability for the fusion detection system is 0.414 2

much higher than that of single detector

which verifies the validity of the calculation method of fusion system for target detection probability. It proves that the fusion image quality and the spectral characteristics of goal itself play important roles for target detection probability. Moreover

the experiment results of the model is accord with the human visual characteristics as well.

关键词

Keywords

references

［1］MEITZLER T J,KISTNER R W,PIBIL W T,et al.. Computing the probability of target detection in dynamic visual scenes containing clutter using fuzzy logic approach［J］. Optical Engineering, 1998, 37(7): 1951-1959.［2］汪朝群.雷达/红外成像双模导引头的联合探测概率研究［J］. 红外与激光工程,2003,32(3):221-224.WANG CH Q. Study on joint probability of detection for radar/IR integrated dual-model seeker ［J］. Infrared and Laser Engineering, 2003, 32(3):221-225.(in Chinese)［3］张必银,张天序,刘纯胜. 图像恢复算法目标获取有效性的评估方法［J］.红外与激光工程,2008,37(1):151-155. ZHANG B Y,ZHANG T X,LIU CH SH. Method of evaluating the restoration algorithms effects on target acquisition from turbulence-degraded images［J］. Infrared and Laser Engineering, 2008, 37(1):151-155.(in Chinese)［4］刘磊,钱芸生,邱亚峰,等.激光助视/微光夜间驾驶仪设计及野外试验［J］. 红外与激光工程,2007,36(3):361-364.LIU L,QIAN Y SH,QIU Y F,et al..Field experiment on the performance of LLL night vision instrument for drive with laser illuminator ［J］. Infrared and Laser Engineering,2007,36(3):361-364.(in Chinese)［5］YUAN Y H,CHANG B K,ZHANG J J,et al.. Real-time implementation of visible and infrared image fusion and new measure based on spectral information［J］. Proc.SPIE, 2009, 7383: 73830S-1-73830S-7.［6］李蔚, 宗志园, 常本康. S25光电阴极与景物反射光谱的光谱匹配系数［J］. 光学学报, 2000, 20(2): 279-282.LI W, ZONG ZH Y, CHANG B K. Spectral matching factors of S25 photocathodes for reflecting spectrum of objects ［J］. Acta Optica Sinica，2000, 20(2): 279-282.(in Chinese)［7］邵明省,杜广朝. 基于量子克隆多宇宙算法的图像融合研究［J］.液晶与显示, 2012, 27(6): 837-841.SHAO M SH,DU G CH. Image fusion processing based on multi-universe quantum cloning algorithm［J］. Chinese Journal of Liquid Crystals and Displays., 2012, 27(6): 837-841.(in Chinese)［8］FAIRCHILD M D. Color Appearance Models ［M］. U.S.A:Addison Wesley Inc, 1998.

Views

570

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Infrared and visible image fusion based on target enhancement and butterfly optimization

Fusion of infrared and visible images combined with NSDTCT and sparse representation

Fusion of infrared and visible images based on target segmentation and compressed sensing

Fusion of infrared and visual images based on non-sampled Contourlet transform and region classification

Fusion of infrared and visible images based on compressive sensing

Related Author

HAO Shuai

LI Tong

MA Xu

HE Tian

SUN Xizi

LI Jiahao

Ming YIN

Pu-hong* DUAN

Related Institution

College of Electrical and Control Engineering， Xi'an University of Science and Technology

School of Mathematics, Hefei University of Technology

School of Computer Science & Engineering, Changchun University of Technology

College of Communication Engineering, Jilin University

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰