SVC bit stream extraction and its applications

Scalable Video Coding (SVC) is the scalable extension of H.264/AVC which extends spatial, temporal and quality scalability on the H.264 video stream. In this thesis, a fast priority index (PID) assignment algorithm is first developed for the MGS (Medium Grain Scalability) packets in SVC. We formulate the index assignment problem as the quantization of the rate-distortion (R-D) slopes of MGS packets, and use the Lloyd-Max algorithm to find the optimal solution. The slope quantization index of a packet is used as its PID. The complexity of our method is much lower than existing method. The quantization-based PIDs facilitate the comparisons of packets from different video streams. Video multiplexing results show that the overall PSNR can be improved up to 1 dB. A fair Peer-to-Peer (P2P) scalable video streaming scheme is also proposed in this thesis. To improve the quality fairness of multiple video streams, we modify our fast PID assignment method where the base-layer quality is also embedded in the Supplemental Enhancement Information (SEI) message of the SVC bit stream, in addition to the quantized rate-distortion slope of each MGS packet. To build a fair ”contribute-and-reward” mechanism for P2P video streaming, we propose a multi-hierarchical topology that is based on peers’ uploading bandwidth. Finally, we combine these two parts to build a SVC-based P2P network, which fully utilizes the quality scalability of SVC, and the end-user quality is determined by its uploading bandwidth contribution. We also propose a caching mechanism for SVC video streaming in the P2P network based on the instant supply and demand estimation. We generalize the previous work from the literature into the SVC case and get the estimation formulation of the supply and demand in SVC video streaming on P2P network. We found that SVC video streaming can further reduce the normalized traffic load from the server compared with AVC video streaming in the same caching strategy set-up.