Generalized Gaussian Distribution Based Distortion Model for the H.266/VVC Video Coder
Hongkui Wang, Junhui Liang, Li Chen Yu, Yiying Gu, Haibing Yin · 2022 IEEE International Conference on Visual Communications and Image Processing (VCIP) · 2022
In versatile video coding (VVC), superior coding performance is achieved with incorporating many advanced coding tools. In this paper, a frame-level coding distortion model is proposed for VVC video coders for the first time. In comparison with the transform coefficient distribution (TCD) of High Effective Video Coding (HEVC), the TCD of VVC has a sharper peak. According to this observation, the TCDs of I, B and P frames are modeled by the probability density function (PDF) of generalized Gaussian distribution (GGD) with three fixed shape parameters. The GGD-based distortion model is then derived with a sliding window-based strategy, i.e., the frame-level coding distortion is formulated as the function of the distribution parameter of frame-level TCD and the quantization step. The experimental results show that the proposed model achieves accurate results of distortion estimation for VVC coders.