Improved detection probability of low level light and infrared image fusion system

Yuxiang Luo; Rongguo Fu; Junju Zhang; Wencong Wang; Benkang Chang

doi:10.1117/12.2317475

20 February 2018 Improved detection probability of low level light and infrared image fusion system

Yuxiang Luo, Rongguo Fu, Junju Zhang, Wencong Wang, Benkang Chang

Proceedings Volume 10697, Fourth Seminar on Novel Optoelectronic Detection Technology and Application; 106972N (2018) https://doi.org/10.1117/12.2317475
Event: Fourth Seminar on Novel Optoelectronic Detection Technology and Application, 2017, Nanjing, China

Abstract

Low level light(LLL) image contains rich information on environment details, but is easily affected by the weather. In the case of smoke, rain, cloud or fog, much target information will lose. Infrared image, which is from the radiation produced by the object itself, can be "active" to obtain the target information in the scene. However, the image contrast and resolution is bad, the ability of the acquisition of target details is very poor, and the imaging mode does not conform to the human visual habit. The fusion of LLL and infrared image can make up for the deficiency of each sensor and give play to the advantages of single sensor. At first, we show the hardware design of fusion circuit. Then, through the recognition probability calculation of the target(one person) and the background image(trees), we find that the trees detection probability of LLL image is higher than that of the infrared image, and the person detection probability of the infrared image is obviously higher than that of LLL image. The detection probability of fusion image for one person and trees is higher than that of single detector. Therefore, image fusion can significantly enlarge recognition probability and improve detection efficiency.

Citation Download Citation

Yuxiang Luo, Rongguo Fu, Junju Zhang, Wencong Wang, and Benkang Chang "Improved detection probability of low level light and infrared image fusion system", Proc. SPIE 10697, Fourth Seminar on Novel Optoelectronic Detection Technology and Application, 106972N (20 February 2018); https://doi.org/10.1117/12.2317475

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