부산대학교 도서관

In this paper, we introduce a low-complexity fine-granularity scalable (FGS) video encoder that refines both residue and motion information in the quality layers. The current scalable video coding (SVC) draft shows that significant gains can be achieved when each enhancement layer undergoes the motion estimation/motion compensation (ME/MC) process with its own motion vector field (MVF). However, given the high computational cost of ME/MC, a motion-refined FGS scheme can be expensive to implement. The proposed scheme controls the macroblock (MB) mode allowed in the base layer and channels computational resources to refine motion in enhancement layers. Through a proper selection of Lagrangian factor for the generation of the first MVF, it is possible to design a low-complexity FGS encoder that has good overall coding performance. A simplified motion-refinement scheme is also adopted for selected MBs in enhancement layers by exploiting the correlation of MB-type information between successive layers to further reduce the complexity of the FGS encoder. Meanwhile, a framework of rate-distortion-complexity optimization is proposed for the FGS by considering the interpolation complexity during the ME/MC in each layer. The FGS decoder can be simplified through the reduction in the number of interpolations.