Rate-Distortion-Optimization-Driven Quantization Parameter Cascading for Screen Content Video Coding Using VVC

Screen content videos (SCVs) have been widely used in television broadcasting, video conferencing, online education, and other fields. VVC is a new generation video coding standard for SCVs, where the quantization parameter (QP) is one of the key coding parameters that significantly affects the coding efficiency of SCVs. The method of selecting optimal QPs for pictures located at different temporal layers is called quantization parameter cascading (QPC). The QPC method recommended by VVC test model, i.e., VTM, does not take into account the impact of video content characteristics on QP selection, resulting in lower coding efficiency of SCVs. To address this issue, a QPC method driven by the rate-distortion (R-D) optimization for SCVs (QPC-SCV), was proposed. Combining experiments and the hybrid coding framework principles of VVC, a novel R-D cost function applicable to the SCV coding characteristics was first established and validated, where the spatiotemporal content characteristics of SCVs were evaluated to predict the model parameters. Then, a video motion form classification and particle swarm optimization were further proposed to effectively solve the R-D cost function and obtain optimized QPs. Compared with the QPC recommended by VTM, the QPC-SCV improves the coding efficiency of SCVs while reducing the coding time. For all test sequences, the average BD-rate corresponding to the QPC-SCV is −6.90%, and the average coding time is reduced by 4.56%.