With the development of multimedia equipment and the increasing demand for high-quality video applications, the traditional video coding standard, H.265/High Efficiency Video Coding (HEVC), can no longer effectively satisfy the requirements. To promote the development of high-quality video, a new generation video coding standard, H.266/Versatile Video Coding (H.266/VVC), is established, and it is the inheritance and development of H.265/HEVC. It not only retains many mature technologies and methods in HEVC but also adds some new coding tools, such as wide-angle prediction and Multitype Tree (MTT) partition structure. The MTT partition structure brings a more flexible partition method of Coding Unit (CU), but the accompanying increase in computational complexity is unacceptable. In order to ensure an effective balance between coding efficiency and coding quality, a fast CU partition algorithm based on texture is proposed in this paper. First, the texture complexity of the neighboring CU is used as a threshold for evaluating the complexity of the current CU, so as to skip the unpromising depth. Then, the gradient features are extracted to determine whether the Quad-Tree (QT) partition is executed. Finally, the improved Canny operator is used to extract edge features, and the partition mode in the horizontal or vertical direction is excluded. The algorithm was embedded in VTM7.0, and the video sequences with different resolutions were tested under general experimental configuration. Simulation experiment results show that the average time saving of this method reached 50.56% compared with the anchor algorithm. At the same time, the average BDBR is increased by 1.31%.

中文翻译：

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H.266 / VVC基于纹理的快速CU分区决策

随着多媒体设备的发展以及对高质量视频应用的需求不断增长，传统的视频编码标准H.265 /高效视频编码（HEVC）不再能有效满足要求。为了促进高质量视频的发展，建立了新一代视频编码标准H.266 /多功能视频编码（H.266 / VVC），它是H.265 / HEVC的继承和发展。它不仅在HEVC中保留了许多成熟的技术和方法，而且还添加了一些新的编码工具，例如广角预测和多类型树（MTT）分区结构。MTT分区结构带来了更灵活的编码单位（CU）分区方法，但是随之而来的计算复杂性增加是不可接受的。为了保证编码效率和编码质量之间的有效平衡，提出了一种基于纹理的快速CU划分算法。首先，将相邻CU的纹理复杂度用作评估当前CU的复杂度的阈值，从而跳过无用的深度。然后，提取梯度特征以确定是否执行四叉树（QT）分区。最后，使用改进的Canny算子提取边缘特征，并排除水平或垂直方向上的分区模式。该算法已嵌入VTM7.0中，并在常规实验配置下测试了不同分辨率的视频序列。仿真实验结果表明，与锚定算法相比，该方法平均节省时间达50.56％。