To learn how smart video compression eliminates the storage balancing act we spoke to Dilen Thakrar, Product Manager at Oncam
The sheer size of high-quality video content and the amount of valuable data received from surveillance systems impose the need for end users to adopt a camera system that harnesses efficient technology. Regardless of size, many organisations evaluate their IT infrastructure and realise that system storage capacity is deficient. Thus, a double-edged sword is fashioned from aiming to reduce expenditures while maximising storage in the existing system.
Traditionally, recording all data from video streams meant that additional storage and bandwidth was required; or alternatively, only certain portions of the data were saved. How can security teams possibly keep bandwidth and storage levels under control?
Video surveillance system integrators are deploying high-performing cameras that utilise advanced compression technologies, allowing organisations to reduce bandwidth and storage needs without compromising on image quality or losing critical information.
The basics
Video images in their raw state consume large amounts of bandwidth and storage. Video compression algorithms are used to reduce their size while still representing a faithful image with significantly less data. When the images are displayed, they are decompressed once again to restore the original detail as closely as possible. The compression and decompression (codec) standards used are subjected to constant development, refinement and optimisation. H.264 has been the staple of video surveillance for some years, and H.265 is increasing in popularity. However, within these standards there is room for more optimisation and fine tuning to achieve greater compression efficiency with the least impact on image quality. The differentiator between how much storage the compression technology actually saves depends on the ability to analyse the captured content of a scene and determine which aspects of a frame are essential, and which are less important.
Algorithms
Maintaining detailed images with lowered demand for video bandwidth and storage becomes possible with advanced real-time adaptive video encoding technology. With the ability to automatically adapt at its core, this compression technology leverages smart dynamic algorithms to continuously analyse video streams. The result? Reduced bandwidth and increased storage savings.
This technology can intelligently identify what is important and relevant to the scene. Intuitively, the camera’s integral capabilities to enhance image quality are applied to what is categorised as essential. Areas of the frame that are deemed unimportant are then compressed. In advanced systems, operators can also take control of some of the elements of the compression, and tune the analytics it uses for their specific environment.
Read the full article in the October 2020 edition of PSI magazine
