An Efficient Framework of Reference Picture Resampling (RPR) for Video Coding

In Versatile Video Coding (VVC), reference picture resampling (RPR) is supported to change resolution without inserting an instantaneous decoder refresh (IDR) picture or intra random access picture (IRAP). The introduction of RPR enables VVC to adapt to unstable network conditions, which benefits real-time application scenarios a lot. However, the existing bitrate leap and the low quality of the upsampled frames are the bottlenecks of promoting its application. In this paper, we propose an efficient framework to alleviate bitrate surges and further improve the coding performance. The contributions of this paper mainly include the following three aspects. Firstly, it is proved theoretically and statistically that the temporal long-distance high-resolution (HR) reference pictures can provide better prediction than temporal short-distance low-resolution (LR) reference pictures when the temporal distance between them is less than a threshold. Secondly, motivated by the theoretical analysis, existing HR reference pictures in the reference pictures list (RPL) are used to replace LR reference pictures and an adaptive decision on the number of HR reference pictures kept in RPL is applied. Thirdly, an adaptive upsampling filter (AUF) is proposed to restore pictures with the original resolution more accurately. Simulation results show 15.09% BD-rate savings on average can be achieved for the 2:1 scaling ratio under RPR configurations. For the 1.5:1 scaling ratio, the BD-rate saving is 8.14%. Besides, the bitrate surge in RPR is reduced greatly. About 25% bits reductions on average at the leaping point can be observed and the bits decrease rate is up to 50% for sequences with little and slow motion.