Transform coefficient distribution modeling based frame-level adaptive rate control for VVC.

Rate control is a key issue in the research of video coding optimization. In this work, we propose a statistical modeling based frame-level distortion estimation model and a distortion dependency based rate control optimization algorithm for Versatile Video Coding (VVC). VVC has incorporated into more advanced coding tools, resulting in the distribution of transform coefficient more sharper. In response to this phenomenon, the TCD of VVC is modeled by the probability density function (PDF) of Cauchy distribution and generalized Gaussian distribution (GGD) individually. Then, a sliding window-based frame-level distortion model is proposed, which is used for derivation of inter-frame distortion dependency factor. According to the derived distortion dependency factor, a frame-level rate control optimization algorithm is presented to update the coding parameters in practical coding process. Experiments have shown that the proposed method could effectively improve rate–distortion performance, achieving an average rate distortion performance improvement of 0.72% in sequences blow 4K resolution, and 1.47% in 4K sequences in low delay P frame (LDP) configuration. • The TCDs of I, B and P frames are modeled by the probability density functions of generalized Gaussian distribution and Cauchy distribution. • The mapping relationship between coding distortion and the quantization step is further investigated. A frame-level distortion–quantization (D–Q) model is then established with a sliding window strategy. • The infer-frame distortion dependency is analyzed and applied to the optimization of frame-level bit allocation. Experimental results show that the proposed RC optimization algorithm could improve the RD performance significantly in LDP configuration. [ABSTRACT FROM AUTHOR]