The objective of scalable video coding is to enable the generation of a unique bitstream that can adapt to various bitrates,
transmission channels and display capabilities. The scalability is categorised in terms of temporal, spatial, and
quality. To improve encoding efficiency, the SVC scheme incorporates inter-layer prediction mechanisms which
increases complexity of overall encoding.
In this paper several conditional probabilities are established relating motion estimation characteristics and the mode
distribution at different layers of the H.264/SVC. An evaluation of these probabilities is used to structure a low-complexity
prediction algorithm for Group of Pictures (GOP) in H.264/SVC, reducing computational complexity whilst
maintaining similar performance. When compared to the JSVM software, this algorithm achieves a significant reduction
of encoding time, with a negligible average PSNR loss and bit-rate increase in temporal, spatial and SNR scalability.
Experiments are conducted to provide a comparison between our method and a recently developed fast mode selection
algorithm. These demonstrate our method achieves appreciable time savings for scalable spatial and scalable quality
video coding, while maintaining similar PSNR and bit rate.