Fast mode decision in fine granularity scalability motion refinement

In this paper, we describe a fine granularity scalable (FGS) video coding scheme that refines both residue and motion information in the quality layers. Significant gains can be achieved when each enhancement layer undergoes the motion compensation, prediction process with its own motion vector field (MVF). However, a motion refined FGS scheme involves a motion estimation process for each enhancement layer of the scalable video. Given the high computational cost of motion estimation in H.264, encoders can be computational expensive to implement. Our proposed scheme carries out a simplified motion refinement scheme for enhancement layers, exploiting the correlation of motion information between successive layers through macroblock (MB) type refinement. By restricting the MB type of FGS layer MB according to the MB type of base layer MB, time required for encoding FGS layers can be reduced. Through controlling the macroblock modes of macroblock in both the base and the enhancement layers, the encoding time can be substantially reduced with minimal impact on coding efficiency. The encoder optimization scheme we describe is especially effective when encoding a video with a low bitrate base layer and a large range of extractable bitrates.