Macroblock-based temporal-SNR progressive fine granularity scalable video coding
- Xiaoyan Sun ,
- Feng Wu ,
- Shipeng Li ,
- Wen Gao ,
- Ya-Qin Zhang
IEEE International Conference on Image Processing (ICIP) |
In this paper, we proposed a flexible and efficient architecture for scalable video coding, namely, the macroblock (MB)-based progressive fine granularity scalable video coding with temporal-SNR scalabilities (PFGST in short). The proposed architecture can provide not only much improved coding efficiency but also simultaneous SNR scalability and temporal scalability. Building upon the original frame-based progressive fine granularity scalable (PFGS) coding approach, the MB-based PFGS scheme is first proposed. Three INTER modes and the corresponding mode selection mechanism are presented for coding the SNR enhancement MBs in order to make a good trade-off between low drifting errors and high compression efficiency. Furthermore, temporal scalability is introduced into the MB-based PFGS, which forms the MB-based PFGST scheme. Two coding modes are proposed for coding the temporal enhancement MBs. Since it would not cause any error propagation if using the high quality reference in the temporal enhancement MB coding, the coding efficiency of the PFGST is highly improved by always choosing the most suitable reference for the temporal scalable coding. Experimental results show that the MB-based PFGST video coding scheme can significantly improve the coding efficiency up to 2.8dB compared with the FGST scheme adopted in MPEG-4, while supporting full SNR, full temporal, and hybrid SNR-temporal scalabilities according to the different requirements from the channels, the clients or the servers.