Fast Multi-Layered Prediction Algorithm For Group Of Pictures In H.264/Svc

The objective of scalable video coding is to enable the generation of a unique bitstream that can adapt to various bit-rates, 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.