|A lower bitrate reduces bandwidth and |
High definition and megapixel cameras provide more detailed images with more useful information, but this can come at a cost. The volume of data being transported and stored rises significantly. The bandwidth demand that this places on the network and the increase in required storage capacity adds significantly to the total IP system costs. The best place to reduce these costs is at the source – in the camera – and this is done by lowering bitrates.
Bitrates can be lowered, in part, by reducing noise. Noise can be interpreted as motion, which makes it the most detrimental factor in clogging the encoding process. It leads directly to exaggerated bitrates for images.
Optimising bitrates to reduce bandwidth
Classic noise reduction can take two forms. Spatial noise reduction averages the pixels within a frame to reduce noise, while temporal noise reduction involves averaging pixels over several frames to cancel out noise artefacts. This is very effective for static images but can cause problems when there is motion. If temporal noise reduction is applied to moving objects, ghosting may be visible in the image.
By combining spatial and temporal noise reduction with the ability to dynamically adjust them based upon light levels and identification of moving objects, images with the least amount of noise, greatest amount of detail and lowest bitrates can be produced. Bitrates can be optimised by tuning the degree of noise reduction based upon an analysis of important objects moving through the camera’s field of view. When the scene is quiet or no motion is present, bitrates are minimised. When an important object is detected, bitrates increase to capture maximum details. The result is that network bandwidth requirements remain at a lower level until something important happens in a scene. Bandwidth is only being consumed at higher levels when increased scene detail may be needed.
Other forms of bitrate reduction
By selecting regions in a scene, and adapting compression ratios, a lower average bitrate can be achieved without the requirement for a constantly low compression ratio for the entire scene
Some HD and megapixel security cameras will, by default, restrict bitrates. Frequently, this is done via constant bitrate. Constant bitrate keeps it at a fixed level. This can result in an always-high bitrate, or when restricted to a low bitrate, it can result in an image quality that is never at its best.
Variable bitrate, on the other hand, establishes a pre-defined level of image quality which is maintained regardless of whether or not there is motion in a scene. Bitrates will fluctuate depending on the scene and the presence of movement.
Dynamic noise reduction as described above operates on the same principle as variable bitrate but with added intelligence to make smart decisions based on the presence or absence of motion. This can deliver up to 50 percent bitrate reduction over standard variable bitrate in scenes without motion.
In addition to noise reduction, region prioritisation can further lower bitrates. With region prioritisation, you are adapting the encoder compression ratio for various regions of an image. Multiple regions in a scene can be defined, each of which is assigned compression level parameters. An unimportant region can be set to use more compression and thus reduce bitrates, while important regions can be assigned a lower compression ratio to show more details.
Take a typical outdoor scene surrounding an entranceway. Areas showing sky could be set as unimportant for higher compression. The area surrounding the building entrance could be set as important and assigned a lower compression ratio to ensure facial characteristics and other identifying details are captured. Finally, the driveway or road next to the entrance could be set for normal compression.
By selecting regions in a scene, and adapting compression ratios, a lower average bitrate can be achieved without the requirement for a constantly low compression ratio for the entire scene.
Reducing costs with dynamic noise reduction
Combining noise reduction and prioritising the regions of a scene produces measurable results. The key benefit of this combination is that you get significantly lower bitrates without loss of image quality. A lower bitrate, in turn, reduces bandwidth and storage requirements.
Ultimately, the solution that provides the highest quality video with the lowest bandwidth and storage requirements will often be the most desirable choice for the customer
Let’s use an example of a shopping mall with 200 surveillance cameras spread throughout the indoor and outdoor areas of the facility. If the requirement is for 1080p HD cameras recording continuously for 12 hours each day and then recording when there is motion after the mall is closed, you’ll need nearly 70 TB of storage for video streamed at 10 frames per second and retained for 30 days. Using cameras that employ dynamic noise reduction in this scenario could save you more than 7 TB in required storage capacity. This can translate into more than $10,000 worth of cost-savings depending on the storage devices being used. Additional savings could also be achieved by adding region prioritisation to specific scenes to further reduce the average bitrate of those images.
For small systems, using dynamic noise reduction and region prioritisation can translate into the ability to record video at a higher frame rate for smoother video when moving objects are present, while still achieving the desired retention time and budget.
For this example, think about a typical 10-camera installation at a retail store. Using 10 720p HD indoor cameras recording continuously for 12 hours each day and then recording when there is motion after the shop is closed, you can store video streamed at 10 frames per second for seven days using a 4TB storage appliance. Now, consider the same scenario using dynamic noise reduction. With dynamic noise reduction, you could stream video at 20 frames per second and achieve the same retention time using the same 4TB storage appliance. You get smoother motion video for the same cost.
The ability to reduce bitrates and therefore bandwidth and storage requirements will become even more important as the industry moves toward the next generation of imaging: 4K ultra HD resolution with even higher data volumes and therefore higher bandwidth and storage requirements. Ultimately, the solution that provides the highest quality video with the lowest bandwidth and storage requirements will often be the most desirable choice for the customer.