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Throwing light on the use of IR in IP

There is a simple premise that impacts the performance and effectiveness of any camera installation: if there is no light, there can be no picture. Whether analogue or IP (where encoding algorithms such as H264 encode the analogue video for use on digital IP systems), virtually all CCTV cameras will produce usable surveillance images under well-lit daytime conditions.

But since today’s security systems require 24/7 operation, it is how a camera performs during the vulnerable hours of darkness that determines overall system effectiveness. Night-time is after all the time when the vast majority of criminal activity occurs.

Many cameras today have very low lux ratings, often in the range of 0,1 lux. While these camera’s specifications will suggest effective operation under low light, it is generally accepted in the security industry that low-light environments result in noisy, low-quality images. When light levels decrease, there is a corresponding increase in the demand for bandwidth, often used synonymously with the term bit rate which is defined as the amount of space required by the network in one second. Generally speaking, and assuming all other factors are equal, night-time imaging requires greater bandwidth than daytime imaging.

Ian Crosby

Automatic gain control

To understand the reasons behind this higher bandwidth requirement in low light, we need to consider automatic gain control (AGC), a camera technology that increases signal strength under low light conditions. AGC works simply by amplifying the image; however, the effect of the amplification is an increase in the video signal, and the subsequent noise. As a scene darkens, AGC is activated and image noise increases. The darker it gets, the more AGC increases in magnitude, and even more noise is created in the process. Eventually, the night-time image is obscured by snow and graininess. Under these conditions, bit rates can be many times greater than the daytime bit rate for static, non-moving images.

To understand why there is a rise in bit rate, it is important to have a basic understanding of how compression algorithms work. The basic principle of compression is to eliminate superfluous information to reduce file size. All compression requires a compromise between image quality and file size. Higher compression ratios deliver smaller file sizes but lower quality images; conversely, lower compression ratios produce higher quality images but larger file sizes.

Today’s popular compression engines typically incorporate JPEG, MPEG or M-JPEG. Most current, of course, is the new H264 algorithm that uses some 30% less bandwidth than MPEG4 compression technology which is itself 80% more efficient than MJPEG. All, however, share common reduction principles: irrelevancy reduction which removes parts of the video signal not noticeable by the human eye, such as subtle colour changes; or redundancy reduction which removes duplicated information either from the same frame or between frames, such as large uniform areas of colour or stationary objects.

Therefore, noise caused by AGC interferes with compression algorithms used in today’s IP encoders. More precisely, compression algorithms interpret the snow and graininess of AGC-enhanced images as useful information (such as image details or motion) that cannot be reduced by either irrelevancy or redundancy. Consequently, night-time images are less compressed and generally larger in file size. From this understanding, it is clear that there is a direct relationship between night-time performance, compression and bit rates.

Combining IR with IP

At first, it seems that the quickest fix would be to disable AGC. The strategy would indeed reduce bit rate, but at the expense of image detail. Doing so would result in very poor – if not useless – night-time images, and the whole purpose of installing CCTV cameras would be lost.

The best solution to ensure effective night-time performance of IP-based systems is to apply infrared illumination to a scene. Providing the camera with the right amount of infrared illumination will ensure that night-time images are high-signal, low-noise. Under these conditions, AGC becomes unnecessary and compression algorithms within encoders, DVRs and other IP equipment work efficiently.

In most applications, frame rates and resolution are typically altered to suit the application requirements. For example, if either network bandwidth or storage space is insufficient, a common strategy is to reduce the frame rate, reduce the resolution or both.

However, there are disadvantages to this approach. Sacrificing frame rate and resolution results in low-quality choppy video that may miss critical moments in a security event. Additionally, low frame rate and resolution often defeat video analytics software. For high-level critical security projects, the better strategy is to upgrade storage and bandwidth capabilities to retain the integrity of the surveillance video.

The addition of active-infrared replaces noisy night-time images with high-fidelity night vision by providing invisible light for the camera to see. High AGC is not triggered and bandwidth requirements remain similar to daytime levels.

When comparing the effects of infrared illumination from a low light scene (<1 lux) to a scene well exposed to infrared illumination, tests have shown bit rate reductions ranging from 48% to 91%. The variation in magnitude of reductions may be attributed primarily to differences in ambient visible lighting levels. The results of these same tests reveal a clear trend of less pronounced bit rate reductions as the ambient lighting conditions became brighter, making infrared illumination less important in video bandwidth. What they show also is that infrared illumination can actually be used as a bit-rate reducing tool under low-light conditions.

At the most basic level, infrared illumination is light. Although invisible to the human eye – which would see a completely dark scene – infrared illumination is a form of light that modern surveillance cameras can use to create images. Precisely because it is light, infrared illumination prevents noisy images and subsequently the chain of events that cause high bit rates. Low-noise (or what can be considered high quality) images require significantly less bandwidth than noisy (low quality) images.

Although infrared illumination provides a field-proven solution for night-time surveillance, its possible application in terms of bandwidth management may come as a surprise. But given that disk space is one of the most expensive components of CCTV security, that surprise will at least be a pleasant one, and indeed encourage risk managers to consider IR as an effective strategy for reducing storage demands in IP encoder applications.

Bandwidth and storage are directly related

If video is being transmitted at a certain bit-rate across a network to be stored, then it will consume disk space at exactly the same rate. For example, a 1 Mbps video stream will use 1 Mb (Megabit) of space in one second, or about 1/8 = 0,125 Megabytes per second, which equates to 0,125 x 3,600 = 450 Megabytes per hour (about 11 GB per day or 75 GB per week).

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