Scalability adaptation for optimisation of coding efficiency of SVC-based video

The explosion of interest in consuming rich multimedia content resulted in a growing demand for technologies that enable seamless access over any network using any terminal without affecting the viewing experience. Scalable Video Coding is considered to be one of the key technologies that will improve the accessibility to video resources through adaptation at network nodes at a negligible computational cost. State-of-the-art video coding technologies enable a comprehensive set of scalability options. However, the trade-off of having such enriched set of scalability options is the reduced compression efficiency and increased encoder/decoder
complexity. This trade-off can be mitigated if the encoder has prior knowledge of the scalability options and levels that are actually needed at a given time. It is possible to achieve this goal in a closely monitored system, such as a Virtual Collaboration System (VCS), in which users and their usage environment are known. This paper
proposes a framework to determine the scalability options and levels for encoding scalable video for VCS. Simulation results highlight the benefits of the proposed framework