Efficient video coding with hybrid spatial and fine-grain SNR scalabilities

Abstract

A flexible and effective macroblock-based framework for hybrid spatial and fine-grain SNR scalable video coding is proposed in this paper. In the proposed framework, the base layer is of low resolution and is generally encoded at low bit rates with traditional prediction based coding schemes. Two enhancement layers, i.e., the low-resolution enhancement layer and the high-resolution enhancement layer, are generated to improve the video quality of the low-resolution base layer and evolve smoothly from low resolution to high resolution video with increasingly better quality, respectively. Since bit plane coding and drifting control techniques are applied to the two enhancement layers, each enhancement bitstream is fine-grain scalable and can be arbitrarily truncated to fit in the available channel bandwidth. In order to improve the coding efficiency and reduce the drifting errors at the high-resolution enhancement layer, five macroblock coding modes with different forms of motion compensation and reconstruction, are proposed in this paper. Furthermore, a mode decision algorithm is developed to select the appropriate coding mode for each macroblock at the high-resolution enhancement layer. Compared with the traditional spatial scalable coding scheme, the proposed framework not only provides the spatial scalability but also provides the fine granularity quality scalability at the same resolution.