Efficient Rate Control in Versatile Video Coding With Adaptive Spatial-Temporal Bit Allocation and Parameter Updating

Despite the fact that Versatile Video Coding (VVC) has achieved superior coding performance, two major problems remain for the rate control (RC) model in VVC. First, the regions concerned by human eyes are not clear enough in the coded video due to the deviation between the target bit allocation strategy of the coding tree unit (CTU) in RC and the human visual attention mechanism (HVAM). Second, there are significant quality fluctuations in the coded video frames due to the inappropriate updating speed. To address the above problems, we propose an efficient rate control (ERC) model. Specifically, in order to make the coded video more consistent with the attention of human eyes, we extract texture and motion-based spatial-temporal information to guide the bit allocation at the CTU level. Furthermore, based on the quasi-Newton algorithm and bit error, we propose an adaptive parameter updating (APU) method with the proper updating speed to precisely control the bits per frame. The proposed ERC outperforms the default RC model of VVC Test Model (VTM) 9.1 by saving the average Bjontegaard Delta Rate (BD-Rate) on full-frame video sequences by 3.60% and 4.94% under low delay P (LDP) and random access (RA) configurations respectively, with higher bitrate accuracy. Moreover, the Peak Signal-to-Noise Ratio (PSNR) and actual coded bits per frame in the video coded by the proposed ERC are more stable.

Automated summary

Despite the superior coding performance of Versatile Video Coding (VVC), the rate control (RC) model still faces two major problems. The deviation between the target bit allocation strategy in RC and the human visual attention mechanism (HVAM) results in unclear regions of interest in the coded video. Additionally, inappropriate updating speed leads to significant quality fluctuations in the coded video frames. To address these issues, an efficient rate control (ERC) model is proposed, which extracts spatial-temporal information and utilizes an adaptive parameter updating (APU) method. The ERC outperforms the default RC model of VVC Test Model (VTM) 9.1 in terms of bitrate accuracy, saving the average Bjontegaard Delta Rate (BD-Rate) by 3.60% and 4.94% under different configurations.