Detection probability of infrared and visible image fusion system

被引：5
作者：
Xu, Hui [1 ]
Zhang, Jun-Ju [1 ]
Yuan, Yi-Hui [1 ]
Zhang, Peng-Hui [1 ]
Han, Bo [1 ]
机构：
[1] School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology
来源：
Zhang, J.-J. (zj_w1231@163.com) | 1600年 / Chinese Academy of Sciences卷 / 21期
关键词：
Detection probability; Image fusion; Infrared image; Target detection; Visible image;
D O I：
10.3788/OPE.20132112.3205
中图分类号：
学科分类号：
摘要：
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 0.2948, pIR is 0.1360, but the detection probability for the fusion detection system is 0.4142, 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.
引用
收藏
页码：3205 / 3213
页数：8
相关论文
共 8 条
  • [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, Optical Engineering, 37, 7, pp. 1951-1959, (1998)
  • [2] Wang C.Q., Study on joint probability of detection for radar/IR integrated dual-model seeker, Infrared and Laser Engineering, 32, 3, pp. 221-225, (2003)
  • [3] Zhang B.Y., Zhang T.X., Liu C.S., Method of evaluating the restoration algorithm's effects on target acquisition from turbulence-degraded images, Infrared and Laser Engineering, 37, 1, pp. 151-155, (2008)
  • [4] Liu L., Qian Y.S., Qiu Y.F., Et al., Field experiment on the performance of LLL night vision instrument for drive with laser illuminator, Infrared and Laser Engineering, 36, 3, pp. 361-364, (2007)
  • [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, Proc. SPIE, 7383, (2009)
  • [6] Li W., Zong Z.Y., Chang B.K., Spectral matching factors of S25 photocathodes for reflecting spectrum of objects, Acta Optica Sinica, 20, 2, pp. 279-282, (2000)
  • [7] Shao M.S., Du G.C., Image fusion processing based on multi-universe quantum cloning algorithm, Chinese Journal of Liquid Crystals and Displays, 27, 6, pp. 837-841, (2012)
  • [8] Fairchild M.D., Color Appearance Models, (1998)
1