Throwing Light on IR for IP Video

Throwing Light on IR for IP Video

Ian Crosby of Bosch Security Systems discusses IR illumination in an IP surveillance environment and its positive effect on bandwidth management.


A simple premise impacts the performance and effectiveness of any camera installation: if there is no light, there can be no picture. Whether analog or IP, virtually all 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.


Many cameras today have low-lux ratings, often in the range of 0.1 lux. While these camera specifications suggest effective operation under low light, dark environments result in noisy, low-quality images.


When light levels decrease, there is an increase in the demand for bandwidth or bit rate, defined as the amount of space required by the network in one second. In general, nighttime imaging requires greater bandwidth than daytime imaging.


Automatic Gain Control
To understand why low light requires higher bandwidth, we need to consider automatic gain control (AGC), which increases camera signal strength under low-light conditions. AGC amplifies the image, increasing the video signal and subsequent noise. As a scene darkens, AGC is activated and image noise increases. The darker it gets, the more AGC increases in magnitude, and more noise is created. Eventually, the nighttime image is obscured by “snow” and graininess. Under these conditions, bit rates can be many times greater than the daytime bit rate for static images.


To understand why there is an increase in bit rate, it is important to know how compression algorithms work. The basic principle of compression is to eliminate superfluous information to reduce file size.


Today's compression engines incorporate JPEG, MPEG or M-JPEG. The H.264 algorithm uses 30 percent less bandwidth than MPEG-4, which is 80 percent more efficient than M-JPEG. All share common reduction principles: irrelevancy reduction, which removes unnoticeable parts of the video signal, such as subtle color changes. Another is redundancy reduction, which removes duplicated information either from the same frame or between frames, such as large uniform areas of color or stationary objects.


Noise caused by AGC interferes with compression. Compression algorithms interpret the snow of AGC-enhanced images as useful information. Consequently, nighttime images are less compressed and larger in file size.


Combining IR with IP
It seems the quickest fix would be to disable AGC. The strategy would reduce bit rate, but at the expense of image detail. Doing so would result in poor nighttime images, defeating the purpose of installing cameras.


The best solution for effective nighttime performance is IR illumination. Providing the camera with the right amount of IR illumination will ensure nighttime images are high signal, low noise. AGC becomes unnecessary and compression algorithms work efficiently.


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


However, this approach has disadvantages. 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 critical security projects, it is better to upgrade storage and bandwidth capabilities to retain the integrity of the surveillance video.


Active IR replaces noisy nighttime images with high-fidelity night vision by providing invisible light for the camera to see. High AGC is not triggered and bandwidth remains similar to daytime levels.


When comparing a low-light scene to a one with IR, tests have shown bit rate reductions from 48 to 91 percent. The variation in reduction rate can be attributed to ambient light. These tests reveal less pronounced bit rate reductions as the ambient light became brighter, making IR less important. The tests show IR can be used as a bit-rate reducing tool under low-light conditions.


IR illumination is light. Although invisible to the human eye — which would see a completely dark scene — it is a form of light that surveillance cameras can use to create images. IR prevents noisy images and subsequently high bit rates. Low-noise or high quality images require less bandwidth than noisy ones.


Although IR provides a field-proven solution for nighttime surveillance, its application for bandwidth management may come as a surprise. But given that disk space is one of the most expensive components in video surveillance, that surprise is a pleasant one. This encourages risk managers to consider IR as an effective strategy for reducing storage demands.

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