Adaptive Resolution Change Using Uncoded Areas and Dictionary Learning-Based Super-Resolution in Versatile Video Coding

摘要

The concept of Adaptive Resolution Change (ARC) in video coding is already known from former international standards such as MPEG-4 [1]. However, in MPEG-4 linear filters are used for upsampling, which is crucial to coding video at varying resolution. With the rise of machine learning-based super-resolution methods in the last decade, powerful algorithms outperforming conventional upsampling methods were developed. This contribution introduces an ARC concept using un-coded areas within a frame of a video sequence and a Dictionary Learning (DL)-based Super-Resolution (SR) scheme. In this concept, a frame contains a picture at different resolution levels, which are spatially separated by the use of slices and tiles. Generally, a tile can be marked as coded or un-coded. Slices which do not hold any coded tiles are omitted from the bitstream. Thus, only one resolution level needs to be coded, while the other is generated at the decoder side. At the encoder a rate-distortion decision is made in order to decide, which resolution level should be coded. Simulation results show that gains with respect to the Versatile Video Coding (VVC) standard in development can be achieved at low bitrates.