MO Yongchao, LIU Lei, QIAN Yunsheng, HU Chaolong, BAI Xiaofeng, SHI Feng. Improved apparent distance detection model of low-level-lightnight vision system[J]. Journal of Applied Optics, 2023, 44(4): 887-897. DOI: 10.5768/JAO202344.0406002
Citation: MO Yongchao, LIU Lei, QIAN Yunsheng, HU Chaolong, BAI Xiaofeng, SHI Feng. Improved apparent distance detection model of low-level-lightnight vision system[J]. Journal of Applied Optics, 2023, 44(4): 887-897. DOI: 10.5768/JAO202344.0406002

Improved apparent distance detection model of low-level-lightnight vision system

  • Apparent distance is an important parameter to evaluate the performance of low-level-light (LLL) night vision imaging system. With the development of LLL night vision detection technology, the simulation results of the classical apparent distance model show some deviations from the actual measurement data, especially the simulation results are not ideal under the low illumination of 10-3 lx, which causes great obstacles to the practical application of the LLL night vision system. Aiming at this problem, the classical apparent distance model was modified from three aspects: the first is considering the influence of atmospheric transmittance on the apparent distance of LLL night vision system and modifying the atmospheric transmittance factors in the classical apparent distance model, the second is optimizing the apparent distance model based on noise factors of image intensifier, the third is considering the influence of human visual transmission characteristics on the apparent distance of LLL night vision system, and the simplified human visual system was added into the transfer function model of the system. The improved apparent distance model was derived, and its effectiveness as well as practicability were verified by the field test data, which had certain guiding significance for the design, evaluation and application of LLL night vision system.
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