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Pete DeAngelis and Paul Bodell of IQinVision share their thoughts on choosing compression algorithms based on user requirements and CCTV system environment considerations.

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In the first article of this series, we covered the basics between temporal and frame-based compression and identified nine factors a decision maker should consider when in the market for a high quality network video surveillance system. The nine factors are:

1. RESOLUTION [User Requirement] (Article 1)
2. FRAME RATE [User Requirement] (Article 1)
3. WEATHER [Video Environment]
4. LIGHTING [Video Environment]
5. SCENE MOTION [Video Environment]
6. OBJECT SPEED [Video Environment]
7. CAMERA MOTION [Video Environment]
8. RECORDING [User Requirement] (to be discussed in article 3 of this series)
9. LIVE VIEWING [User Requirement] (to be discussed in article 3 of this series)

The considerations fall into two categories: "User Requirement" which will vary depending on the customer's preferences, and "Video Environment," which are the variables in an application that will likely have an impact on your video.

In this article, we will review considerations 3 through 7, comprising all factors for the video environment and their impact on system variability. To frame the discussion, it is our position that a video system should always be optimized to achieve a desired image quality, and then adjusted for frame rate to maximize bandwidth and storage efficiencies. When dealing with MJPEG, we encourage a compression setting no lower than medium (MJPEG= 50). With H.264, we recommend nothing lower than the MAIN profile and that you allow the bit rate to vary (VBR) to ensure delivery of the best quality image. Remember, the customer is paying for a video recording system that should meet their expectations in all conditions, not just optimal ones. As system designers and architects, we must work diligently to guarantee that the choices made during the design and configuration of the system do not degrade the video's quality during those times when events of interest occur.

3. Weather [Video Environment]

Weather can have many characteristics, but the four elements that have the largest impact on video are rain, snow, changing light and wind. In this section we will consider the impact of rain and snow and we will address changing light and wind in subsequent sections. Video compression treats rain and snow like motion and will do its best to try to reproduce it accurately. With MJPEG, rain and snow have no impact on image quality and very little impact on bandwidth and storage as MJPEG handles each image separately. However, the steady-state bandwidth and storage consumption of MPJEG video will be higher than H.264 when there is no rain or snow. Rain and snow will have a significant impact on H.264 bandwidth and storage as it interprets rain and snow as a 100 percent scene change from one frame to the next.

This means a well-designed network, which properly accounts for the worst-case scenario will budget enough bandwidth for these events -- possibly budgeting the same amount of bandwidth as you would with an MJPEG system. Essentially, you will need to factor into your bandwidth and storage calculations the number of days out of the year you can expect rain or snow. The impact on image quality with H.264 can also be quite profound as the cameras are forced to predict not only the motion associated with the rain and snow, which is typically vertical, but also the motion of any subjects of interest which is often horizontal or diagonal. These extraordinary processing demands can sometimes be too much for a camera to handle and the resulting images will have substantial compression artifacts, often described as blurriness or blockiness.

4. Lighting [Video Environment]

There are two characteristics of lighting that need to be considered when selecting a video compression algorithm; the first is the amount of change in light over time. For static lighting scenes, H.264 can offer excellent efficiencies over MJPEG with minimal image degradation. Scenes where the light is changing, like outdoor scenes, can present some challenges for H.264. Similar to rain and snow, changing light -- whether headlights in the field of view or clouds passing in front of the sun -- can represent large frame-to-frame scene changes. H.264 cameras will respond to this by increasing the bandwidth, in some cases exponentially, and all but the highest broadcast quality HDTV cameras like those found in professional sports will degrade the image quality noticeably.

The other characteristic of lighting that will have an impact is low light. When lighting decreases, cameras have to amplify signals to try and reproduce the image. Anytime you amplify a signal, you introduce noise. For those of you old enough to remember TV before cable, weak TV signals meant a lot of noise or "snow". Today it is no different. While more mature companies are very effective at reducing low-light noise in the camera, at some point it will happen and when this occurs, it behaves exactly like real snow.