What Is the Working Principle of Niankang Night Vision?

With the help of high-sensitivity CMOS sensors that collect weak visible light (such as starlight, moonlight, etc.) in the environment, and then use advanced AI algorithms to perform a series of processing on it in real time, such as noise reduction, complementary color, and enhancement., it can eventually output full-color real images close to daytime effects, rather than turning the picture into green or black and white like traditional night vision devices.‌‌

Compared with traditional night vision devices, its biggest difference lies in the technological route. However, traditional low light night vision devices have a series of hidden dangers of blindness. Their working principle is to first convert external light into electronic signals through photoelectric conversion, greatly increase the intensity of this signal by multiplying it, and then bombard the fluorescent screen to convert the light signal into images that we can see. However, fundamentally, they can only display monochrome black and white images, and the radiation of strong light is also very easy to cause certain "blindness" hazards to the human body. Full color low light night vision devices completely bypass the traditional "blindness" path of image enhancement tubes and take the "high-sensitivity CMOS+AI ISP" route The core difficulty and advantage of the new route of "algorithm" lies in its algorithm - how to suppress noise and restore the color of external light at extremely low illumination.‌‌

Workflow disassembly

Guided by weak light, high-sensitivity sensors can capture weak light such as starlight and moonlight in a dark environment, and even the peripheral light of distant street lights can sense its existence one by one. However, in a closed space such as the depths of a cave in complete darkness, even full-color dim light is difficult to play its due role, so it is more necessary to use thermal imaging or active infrared fill light to see clearly the environment you are in.

Through the deep enhancement of AI, our work has really moved from "smell" to "intimate". With a series of advanced algorithms such as real-time fine noise reduction, color restoration and dynamic range expansion for each frame, it can "predict" near-true colors and finally output a clear full-color picture.

Whenever exposed to strong light from vehicle headlights, street lamps, etc., the night vision device can immediately perform corresponding suppression processing, avoiding the embarrassing situation where traditional night vision devices suddenly turn completely white when encountering strong light sources, and then gradually recover over several seconds.‌‌

Compared with traditional night vision technology

While traditional enhancement tubes such as "green screen" are favored by people for their passive imaging and strong concealment capabilities, they can only output a single green or black-and-white image. For those dynamic images with rich colors, they lose a lot of their appeal to the audience. At the same time, due to the special nature of their operation, they are prone to certain damage to the tubes they carry in strong light. Even more terrifying is that the core components they rely on are mostly imported, resulting in high costs.

However advanced infrared thermal imaging technology may be, it cannot completely replace traditional visible light imaging. It can only work in a completely dark environment, but it can only present a contour image of the temperature of the object being measured. It cannot accurately describe the internal details and color expression, and its cost is relatively high.

However, as an ordinary digital infrared night vision device, it mainly relies on active infrared lights for supplementary lighting, and the image can only be black, white or green. This makes the infrared light easily exposed to external light, greatly reducing its concealment in combat. In addition, it also makes the image quality of the night view it takes relatively rough.

Its passive collection of ambient light has the characteristics of not emitting light, good concealment, and the ability to output full-color images that are close to real colors. It can clearly see the color of clothing, license plate numbers, etc., and its power consumption and weight are also lower.‌‌