Dr. Xuan Liu Profile

Dr. Xuan Liu

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Proceedings Article | 13 December 2024 Paper

Imaging quality comparison system and method of image intensifiers

Ruiqiang Li, Xuan Liu, Weiqi Jin, Yuyang Li, Li Li, Jinneng Zeng, Qionglian Yang

Proceedings Volume 13496, 134960S (2024) https://doi.org/10.1117/12.3047855

KEYWORDS: Image intensifiers, Image quality, Imaging systems, Quality systems, Cameras, Video, Night vision, Human-machine interfaces, Computing systems, Displays

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The image intensifier is a type of low-light detector, consisting of three parts: a photocathode installed inside a high vacuum tube, an electron lens, and a fluorescent screen. Currently, there are few evaluation methods for the imaging quality of image intensifiers domestically. To further promote the rapid development of micro-light night vision technology and quantitatively evaluate its imaging qualities, research on quantitative evaluation methods for image intensifiers' imaging qualities has been conducted. An image quality comparison system for image intensifiers is designed, which can adapt to install various image intensifiers with different external dimensions. Meanwhile, a control software for the image intensifiers comparison system is designed to control two image intensifiers for comparison purposes. Additionally, digital image processing techniques are used to assist observers in judging the image quality, thus effectively promoting largescale experiments on image intensifiers imaging qualities comparison. Experimental testing was respectively conducted in indoor environments with illuminance levels of 10^-3 lx and outdoor environments with illuminance levels of 10^-2 lx. Actual testing experiments have shown that the system is convenient and feasible, suitable for various indoor and outdoor scenarios. It can real-time compare the imaging qualities of different models of image intensifiers. Moreover, various evaluation indicators can assist observers in judging imaging details that are difficult for the human eye to discern. This system can provide feedback to guide further optimization of the production and manufacturing processes of image intensifiers, thus promoting the development of low-light night vision technology.

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