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How to determine the authenticity of black light full-color cameras

Views: 28738     Author: Site Editor     Publish Time: 2021-04-27      Origin: Site

How to determine the authenticity of black light full-color cameras?

In recent years, the image quality of smart WiFi cameras has rapidly improved, from infrared cameras, starlight full-color cameras to the current black light full-color cameras. Ordinary users also have higher requirements for the imaging effect of IP cameras, with pixel indices increasing from 2 million or 3 million to 5 million or even tens of millions of pixels. Although pixel improvement is fast, in dark or overly bright environments, smart outdoor WiFi cameras are still prone to capturing blurry or overexposed images, making it difficult for them to capture details.

The application of extreme black light technology has greatly improved the night vision effect of outdoor smart WiFi cameras. When people and objects are in a low light environment, photos taken by WiFi black light full-color cameras can still be in color. This greatly improves the accuracy of monitoring, solves problems such as blurring at night, and further optimizes the monitoring effect.

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The development of smart home WiFi black light full-color cameras has always been based on the advancement of Image Signal Processing (ISP) technology. Traditional ISP technology has limitations in low light and high dynamic range (HDR) conditions, leading to issues such as motion blur and overexposure. These challenges not only fail to meet the growing demand for image capture, but also hinder the development of monitoring and other departments.

However, technology continues to address the issue of full-color imaging at night. Although many people still hold negative views on the shortcomings of traditional ISP, the development of artificial intelligence provides more possibilities for full-color imaging. AI-ISP technology can achieve high-definition full-color imaging under extremely low lighting conditions. Intelligent WiFi/IP pan tilt cameras are evolving from "capture" to "full-color clear capture".

Nowadays, black light full-color cameras have the ability to operate under 0.01 Lux or extremely low lighting conditions. However, achieving black light full-color effects requires specific accessory support, such as large-sized sensors, high-resolution sensors with larger pixels, large aperture, or low video frame rates. These improvements enable intelligent black light full-color cameras to capture more light and color at night. Despite these improvements, nighttime monitoring still often faces challenges such as color saturation below 100%, motion artifacts, increased costs due to large sensors and aperture, and incomplete compliance with industry requirements.

The advancement of AI-ISP technology has completely changed the field of black light full-color imaging, making nighttime full-color monitoring images a reality. Intelligent cameras with AI-ISP functionality can accurately reproduce colors in real time even under 0.01 Lux or extremely low lighting conditions, eliminating the need for white or infrared fill light for intelligent outdoor cameras. By maintaining a color saturation of over 100%, these intelligent full-color outdoor cameras can accurately capture moving objects without any issues of trailing, ghosting, or perspective distortion. The following are six key elements of black light full-color cameras summarized by experts, including low light sensitivity, real-time frame rate, color accuracy, and minimum motion blur, to ensure the highest video performance of intelligent outdoor black light cameras in dark environments.

The Zhangwo True Black Light Full Color Camera G11 meets the six key standards outlined by intelligent camera experts for black light full color cameras, including low light sensitivity, real-time frame rate, color accuracy, and minimal motion blur, ensuring that the intelligent outdoor black light camera can achieve the highest video performance in dark environments, making your night and day as exciting.


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