基于朴素贝叶斯理论的VVC编码单元划分决策

Proceedings of the 2023 5th International Conference on Image Processing and Machine Vision Pub Date : 2023-01-13 DOI:10.1145/3582177.3582188

Leiming Duan, Xiantao Jiang, W. Li, Jiayuan Jin, Tian Song, F. Yu

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引用次数: 0

摘要

通用视频编码(VVC)是采用混合编码模型的最新视频编码标准。与HEVC (High Efficiency Video Coding)标准相比，VVC可以节省50%的比特率。但是，VVC的编码复杂度较高。本文提出了一种快速分割决策算法来降低VVC的编码复杂度，并将CU分割或不分割问题建模为基于朴素贝叶斯理论的二分类问题。该方法在编码效率和编码复杂度之间取得了良好的平衡。实验结果表明，与VVC参考软件模型相比，该算法可将编码时间缩短48.00%，而bd率的损失仅为1.69%。

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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%.

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Proceedings of the 2023 5th International Conference on Image Processing and Machine Vision

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