The trend for artificial intelligence continues to spread worldwide. Its integration into various fields not only yields minor benefits but also influences the development of entire technologies. Night vision is the best example of this. In this area, AI enables improvements in the performance of various devices and opens up new possibilities for improvement. Today, artificial intelligence has become so important in night vision that some experts have already announced the possibility of a next generation of NV devices.
Discussions about a new generation of night view binoculars, monoculars, scopes, and goggles have emerged amid reports that many manufacturers of such equipment are prioritizing AI integration. They aim to improve image quality and expand the capabilities of night vision optics. Some manufacturers have already achieved partial success in these areas. Their NV equipment leverages AI for image processing. Special algorithms that analyze each frame help eliminate noise and other defects, improve clarity, and enhance detail. At the same time, the AI capabilities available today are still insufficient to achieve ideal results, so work on improving them is ongoing.
Artificial intelligence also plays a key role in expanding the functionality of modern night vision devices. Thanks to it, even the most affordable NV goggles, binoculars, and cameras gain a variety of useful features. One of these is object recognition. Using AI algorithms, night vision optics analyze the observed scene and detect people, animals, and various inanimate objects. Furthermore, artificial intelligence in NVDs combines data obtained from various sources, automatically selects optimal settings, provides prompts for control and use of the devices, and much more.
The capabilities of modern night vision devices are severely limited. Artificial intelligence is partly to blame for this. Its imperfections and insufficient integration into optics do not yet provide grounds for calling existing NVDs next-generation devices. However, the chances of reaching a new level are already high in the near future. Many experts and representatives of various manufacturers believe so. According to them, the next generation of night vision devices must eliminate all image defects. Solving this problem will be difficult without the use of AI. Only improved AI algorithms will enable instant image processing and the elimination of various defects. Theoretically, the nature of the defects (poor lighting, adverse weather conditions, incorrect settings, etc.) will not even matter.
The next generation of NVDs must also learn to convert monochrome images into color and guarantee accurate rendition of various shades. Current processing methods don’t achieve perfect results, but this may become the norm in the future. AI will play a key role in this process. Theoretically, it will be able to instantly colorize a monochrome image, selecting the correct colors and shades for every point in the observed scene. More accurate object recognition is another essential component of next-generation night vision devices. Today, AI can already handle this task, but the high error rate still prevents the desired results. Experts believe that more sophisticated algorithms will maximize object recognition accuracy. In the near future, they expect to achieve an error rate of less than 1%.
AI can help achieve another feature that almost all specialists mention when discussing next-generation night vision devices. This feature is called image fusion and involves combining images obtained from all available devices (e.g., IR cameras, thermal imagers, etc.). Theoretically, thanks to AI capabilities, the superposition of one scene onto another will be performed with maximum precision, even in real time. If this happens, next-generation NVDs will be effective under any operating conditions, and the images they generate will be as informative as possible.
The current AI benefits of night vision technology are only a small fraction of the potential advantages. This is why many experts are hesitant to call modern NVDs next-generation devices. A long road of development remains to be covered before they become such. In particular, deeper integration of AI into the operation and various processes of night vision optics is necessary. If this happens, the next generation will become a reality, not a distant future.
