Virtually all CCTV cameras produce usable surveillance images under daytime conditions, but when faced with challenging lighting, some IP cameras encounter issues with image quality and bandwidth management. And, since today’s security systems require 24/7 performance, it is often the nighttime function that determines overall system effectiveness.
CCD and CMOS image sensors are designed to see light -- making pictures or videos in the process. If there is no light, there can be no picture. Many cameras today have very low lux ratings, often in the range of 0.1 lux. While these camera specifications suggest effective operation under low light, the security industry generally accepts that low-light environments result in noisy, low-quality images. As image noise increases, there is a corresponding increase in the demand for network bandwidth -- or the number of bits transmitted in one second.
To understand the reasons behind higher bandwidth in low light, it is important 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 both the video signal and the noise. As the scene becomes darker and darker, AGC increases in magnitude, creating more noise in the process. Eventually, snow and graininess obscure the nighttime image. Under these conditions, bitrates can be many times greater than the daytime bitrates for static, non-moving images.
This rise in bitrates directly correlates to the interference of AGC with compression algorithms used in today’s IP cameras. The basic principle of compression is to eliminate superfluous information to reduce file size. Compression requires a compromise between image quality and file size. Higher compression ratios deliver smaller file sizes but lower quality images. Lower compression ratios produce higher quality images but larger file sizes.
Today’s popular compression engines typically use one of two reduction principles:
- irrelevancy reduction - removes parts of the video signal not noticeable by the human eye, such as subtle color changes
- redundancy reduction - removes duplicated information, such as large uniform areas of color or stationary objects, either from the same frame or between frames
Compression algorithms interpret the snow and graininess of AGC-enhanced images as useful information, such as image details or motion, which cannot be reduced by either irrelevancy or redundancy. Consequently, nighttime images are less efficiently compressed and have larger file sizes.
At first, it seems that the quickest fix to this issue would be to disable AGC. This strategy would indeed reduce bitrates but at the expense of image detail. Doing so would result in very poor -- if not useless -- nighttime images.
In many applications, integrators will alter frame rates and resolution to suit the end user’s bandwidth or storage limitations. For example, if either network bandwidth or storage space is insufficient, a common strategy is to reduce the frame rate, 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 rates and resolution significantly degrade the performance of video analytics software, if used.
The Effects of Adding Infrared
The best solution to ensure effective nighttime performance of IP-based systems is to apply infrared illumination to a scene. Infrared illumination is field-proven technology for high-performance night vision, and its use in today’s surveillance video applications extends into bandwidth management as well.