VVC Coding Unit Partitioning Decision based on Naive Bayes Theory

Versatile Video Coding (VVC) is the latest video coding standard, which uses a hybrid coding model. VVC achieves 50% bitrate saving compared with High Efficiency Video Coding (HEVC) standard. However, the encoding complexity of VVC is higher. In this work, a fast partition decision algorithm is proposed to reduce the encoding complexity of VVC, and the CU splitting or no splitting is modeled as a binary classification problem based on Naive Bayes theory. This method has good performance and balances encoding efficiency and encoding complexity. Experimental results show that, compared with the VVC reference software model, the proposed algorithm can reduce encoding time by 48.00%, while the loss of the BD-rate is only 1.69%.