Zhao Shuai, Shang Xiwu, Wang Guozhong, Zhao Haiwu
School of Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Sensors (Basel). 2023 Jul 7;23(13):6244. doi: 10.3390/s23136244.
Versatile Video Coding (VVC) introduces many new coding technologies, such as quadtree with nested multi-type tree (QTMT), which greatly improves the efficiency of VVC coding. However, its computational complexity is higher, which affects the application of VVC in real-time scenarios. Aiming to solve the problem of the high complexity of VVC intra coding, we propose a low-complexity partition algorithm based on edge features. Firstly, the Laplacian of Gaussian (LOG) operator was used to extract the edges in the coding frame, and the edges were divided into vertical and horizontal edges. Then, the coding unit (CU) was equally divided into four sub-blocks in the horizontal and vertical directions to calculate the feature values of the horizontal and vertical edges, respectively. Based on the feature values, we skipped unnecessary partition patterns in advance. Finally, for the CUs without edges, we decided to terminate the partition process according to the depth information of neighboring CUs. The experimental results show that compared with VTM-13.0, the proposed algorithm can save 54.08% of the encoding time on average, and the BDBR (Bjøntegaard delta bit rate) only increases by 1.61%.
通用视频编码（VVC）引入了许多新的编码技术，例如带嵌套多类型树的四叉树（QTMT），这极大地提高了VVC编码的效率。然而，其计算复杂度较高，这影响了VVC在实时场景中的应用。为了解决VVC帧内编码复杂度高的问题，我们提出了一种基于边缘特征的低复杂度划分算法。首先，使用高斯-拉普拉斯（LOG）算子提取编码帧中的边缘，并将边缘分为垂直边缘和水平边缘。然后，将编码单元（CU）在水平和垂直方向上均分为四个子块，分别计算水平和垂直边缘的特征值。基于这些特征值，我们提前跳过不必要的划分模式。最后，对于没有边缘的CU，我们根据相邻CU的深度信息决定终止划分过程。实验结果表明，与VTM-13.0相比，所提算法平均可节省54.08%的编码时间，且BDBR（Bjøntegaard 比特率增量）仅增加1.61%。
