The impact of the quality of the CCD camera on the network camera Summary: The quality of the CCD camera used by the network camera (network camera server, video server, network video converter, etc.) has a great impact on the bandwidth, and the use of a high-quality CCD camera can greatly reduce The bandwidth of the network camera. 1. Questions raised The development of network camera technology, especially the popularization of broadband networks, has made network-based network monitoring applications popular. The advantages of flexible monitoring and control configuration, tight integration with the information network, and long-distance remote monitoring are unmatched by traditional monitoring. How to correctly master and reasonably use network cameras is a new issue facing users. The main problem in the practical application of network cameras is the first is the image compression technology problem: the second is the network bandwidth data transmission problem. The essence of the so-called solution to the bandwidth problem is how to transmit higher-quality images over a limited bandwidth. Of course, there is also the problem of the improvement (decompression) of computer operating system software management capabilities; the development of image data compression technology and the application of high-speed central processing units, etc. They are all basic technologies to solve the image compression problem of network cameras. The development of many technologies (especially MPEG4) has undoubtedly enabled our network cameras to achieve a greater image compression ratio than before. But is this enough? the answer is negative. 2. Improving the quality of the original reference image is the key to image compression Under certain compression technology and certain application environment, what factors affect the bandwidth of the network camera? This is whether the CCD camera used in the front end of the system can send stable and clean images, that is, each frame is used as a newly added original reference image or as a constant compressible variant image. This factor is often overlooked by everyone. After the unstable and dirty image is input to the network camera, the network camera recognizes the newly added original reference image and is retransmitted. The originally unchanged compressible variated image is misjudged as a newly added original reference image, which appears to have color shift, color roll, picture distortion or roll, interference stripes, noise and so on. Practice has proved that these unstable and unclean images transmitted by network cameras should be transmitted as images without mutation, so the transmission bandwidth occupied by these image data must be very large. Why is there such a result? This should be understood from the principle of image data compression. Image data compression is usually achieved through two links: the first link is the compression of the image size, the smaller the image size, the shorter the image data, so as to achieve the purpose of compressing the amount of data. The second link is the compression of the image formation process, that is, in the continuous image transmission process, we only transmit the changed part of the image, and the relatively static part is not transmitted, which makes the image data shorter and achieves compression. It also reduces the excessive bandwidth. For example, we monitor the situation in a room. When no people or animals are walking in the room, the image we see is still. At this time, the network camera does not need to repeatedly transmit so many same pictures, so the bandwidth occupied by the still state is very small. When someone or an animal is walking, the network camera only needs to transmit the changed part of the image, which greatly shortens the entire image data. Although the image data is shortened, it still faithfully records all the conditions in the room. The basis for the network camera to identify whether the image is still or active is mainly to detect whether the gray level (or color scale) of the image has changed. If there is no change, it is still, and otherwise it is active. However, the factors that affect the gray scale change are not only moving people and objects, but also the light changes and the unstable and unclean image noise signals we mentioned above. In the eyes of network cameras, even if they are still For those rooms that are unstable and unclean, it also considers the mutated picture to increase the image data, which we do not need. 3. Adopt high-quality CCD camera to ensure that the variation image is reduced The use of high-quality CCD cameras to improve the signal-to-noise ratio and achieve high-speed tracking white balance is the key to ensuring that the variated picture is reduced, thereby reducing the bandwidth of the network camera. A picture without noise is a clean picture, and the performance index is a high signal-to-noise ratio. On the contrary, the picture of a CCD camera with a poor signal-to-noise ratio is full of noise, and the position of the noise in the picture is not repeatable, every frame The picture is different. From the perspective of the network camera, each image is a full-screen changing image. The compressed data is the largest and the bandwidth is the most. Experiments show that such picture data is more than 30% larger than clean picture data or even more. This is one of the main reasons for the increase in the bandwidth of many of our users' network cameras. Another parameter is the speed of the CCD camera tracking white balance. This parameter actually reflects the calculation speed index of the DSP chip used in the CCD camera. The DSP calculation speed of the ordinary CCD camera is 100,000 times per second. The high-quality CCD camera The operation speed of the DSP in the system can reach 10 million times per second, and the whole difference is 100 times. What are the benefits of DSP fast? It is easier to think of the problem of color drift, because the speed of calculation directly affects the speed of its tracking of white balance. We can use fluorescent lamp environment to illustrate this problem. The average white balance speed of a CCD camera is usually between 120 milliseconds and 160 milliseconds, which means that it takes roughly 6-8 image fields (50 fields per second in PAL) to complete a white balance change. Such a speed Certainly can't keep up with the change of fluorescent light source. The change of the fluorescent lamp on and off in 1 second is 100 times, that is, it needs to change every 20 milliseconds. Obviously, the general camera can not keep up with this change speed. Therefore, under the environment of the fluorescent lamp, the captured image will produce color shift and The phenomenon of color drift, the original still picture will become a "moving" image with periodic color changes, so the deceived nature is again a network camera. But if the calculation speed of the DSP of the CCD camera is fast, if only one millisecond can be used to balance the change of the white balance, a very stable image can be obtained. The enlightenment of this example is that with the continuous improvement of environmental protection and energy saving requirements, the application of pulsed lighting will also become more and more extensive, and in such a situation, the requirements of the network camera for the computing speed of the DSP of the CCD camera used are It will become necessary, that is to say, the calculation speed of the CCD camera DSP will become an indicator of network monitoring (the same is true of hard disk recorders). It can be seen from the above analysis that a high-quality CCD camera (providing a signal-to-noise ratio of 52db-60db and a DSP operation speed of 10 million times / second) can greatly improve the application quality of network cameras. Of course, the indicators that affect the image quality of the CCD camera also have the sensitivity index of the CCD. A CCD camera with a high sensitivity index can improve the signal-to-noise ratio when the illumination is low. It is worth noting that the clarity index of the CCD camera has little effect on the image quality, but has a great influence on the use of the bandwidth of the network camera. Images with higher definition occupy more storage space, and blindly pursuing the high definition of network cameras not only increases the cost of use, but also increases the transmission, processing, and storage of images. This is an unscientific choice.
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