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Video cameras are constantly appearing in every corner recently because they allow us to monitor things without knowing something, such as a place, a person, and a thing. Camera technology is like a human eye, and objects and scenes can only be seen by feeling and processing the existing light. Just like turning off the lights in the house, we need to work hard to see clearly, many video cameras must deal with low-light environments. If the camera can't overcome the low-light conditions and carry out clear monitoring, placing the camera in the scene may not provide the visibility we need.
The latest developments in video camera technology, especially the development of low-light noise filtering technology, not only enhance the quality of the single still images or frames that make up the video stream, but also enhance the fidelity of the single pixels that make up each frame. The improved filtering technology supports three-dimensional work, which can eliminate visual anomalies in low-light video streams and make the image clear and sharp. Cameras with powerful real-time processors and advanced compression algorithms are usually sharper than human eyes in low light conditions. According to the 2010 FBI Unified Crime Report, 52.8% of violent crimes and 81.7% of property crimes have not yet been cracked1. Cameras equipped with good low-light technology will help reduce this number.
Part of the problem
Video cameras (IP cameras) connected to the Internet are being deployed in various applications. In addition to the commonly used security surveillance cameras implemented in security and law enforcement facilities, cameras are now also widely used in computers, tablets, and smartphones. In addition, more and more vehicles have begun to be equipped with video surveillance systems or on-board black boxes to assist complex operations in narrow corners and enhance vehicle safety. As the basis for these and other applications, IP cameras must frequently provide video streaming in low light, even with auxiliary lighting. This issue is particularly important in security applications.
The video streams provided by IP surveillance cameras used to monitor dark alleys or dark corridors are often blurred, pixelated, unclear, and have poor contrast. Low-quality video streams often cause the face to be unrecognizable or completely miss the events that occur, affecting the practicality of the video security monitoring system. Providing better lighting conditions is generally not feasible, because the lighting itself requires cost and maintenance, and makes the safety monitoring system easy to be noticed.
Finally, the ideal solution is to enhance the low-light performance of the IP camera so that it can achieve higher work efficiency in lower light and provide clear and sharp images. In the following images, one uses low-light performance enhancement technology and the other does not. They can clearly explain how these technologies enhance the application effect of video surveillance systems and other methods.
Figure 1: Video images taken without low-light performance enhancement technology
Figure 2: Video images taken with low-light performance enhancement technology
"Noise" in low-light video signals
The culprit that causes the image quality of IP cameras to deteriorate under low light conditions is "noise". In other words, the camera improperly included the irrelevant signal data of the image due to low light conditions. The artifacts or abnormal data in the signal processing of these cameras can cause the quality of the video stream to deteriorate, the image to be blurred, and the definition to deteriorate. To improve the image quality of video IP cameras working in low-light environments, it is necessary to eliminate this noise as much as possible. By improving the signal-to-noise ratio (SNR) of the video data stream, the camera can provide a clearer image. After the noise is reduced, the signal from the actual objects in the scene will increase and the video image will be clearer. There are several clear sources of noise, each of which must be treated to some degree.
Particle noise Particle noise naturally comes from fluctuations in the hit rate of visible photons hitting the video camera sensor. The number of photons hitting a sensor pixel varies randomly around an average rate proportional to the pixel illumination.
Fixed pattern noise Fixed pattern noise is caused by small changes in the pixels that make up the IP camera sensor. Each pixel reacts differently when it is hit by a visible photon. These differences may come from differences in pixels and color filters, or from differences in circuits connected to pixels.
Read out noise The analog information collected by the video camera light sensor must be converted to digital data for the camera to process. This work is done by an analog-to-digital converter. Read out the noise caused by the incompleteness of the conversion process.
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