Fast CU Partition for VVC Intra-Frame Coding via Texture Complexity

In versatile video coding (VVC), the quadtree with nested multi-type tree (QTMT) partition module significantly improves encoding performance compared to other coding tools. However, it also introduces notable computational complexity in intra-frame coding, occupying over 90% of the encoding time. This paper presents a fast coding unit (CU) partition method based on texture complexity to achieve a balance between compression efficiency and computational complexity for VVC intra-frame coding. In particular, the texture complexity of CUs is quantitatively measured by the ratio of horizontal to vertical gradient and that of sub-block variances. Firstly, directions with higher texture complexity are identified as unlikely coding modes and eliminated from the candidate set. Next, the subblock variances of binary and ternary partitions are compared to determine a fine-grained CU partition pattern, avoiding unlikely partition modes. Experimental results show that our method is simple but efficient, and achieves higher computation efficiency compared to recent machine learning-based and handcraftedbased methods. The implementation of the proposed method is publicly available at https://github.com/csust-sonie/fastCU.