Improving enhancement layer merge mode for HEVC scalable extension
In the HEVC scalable extension (SHVC), the merge mode prediction plays an important role due to its high selection probability and its low associated bitrate. In the SHVC enhancement layer (EL) merge mode prediction, the motion information is selected from the merge candidates, in this case the spatial, temporal, and inter-layer candidates. Therefore, the merge mode prediction is usually inefficient when the motion vector field (MVF) correlation between the merge candidates and the current EL block is low, especially in video sequences containing high motion activity. To address this problem, this paper proposes an improved EL merge mode prediction solution that adaptively refines the motion vector candidates by using both base layer (BL) and EL decoded information and after linearly combines the motion compensated samples with the BL reconstructed samples to achieve a better merge mode prediction quality. Experiments conducted for a rich set of test conditions have shown that significant compression efficiency gains can be achieved with the proposed improved scalable coding solution, notably up to 4.57% in BD-rate savings regarding the standard SHVC quality scalable codec.