在VVC内部编码中对三元树分区的快速决策机制
Jiamin Sun1,2, Zhongjie Zhu1,2, Renwei Tu1
1Key Laboratory of Industrial Vision and Industrial Intelligence, Zhejiang Wanli University, Ningbo, China.
PloS one
|February 6, 2026
概括
本研究介绍了多功能视频编码 (VVC) 的快速决策机制,以优化三元树 (TT) 分区. 该方法使用图像特征来预测最佳模式,显著加快编码速度,同时保持质量.
科学领域:
- 视频压缩技术视频压缩技术.
- 数字图像处理是数字图像处理.
- 机器学习用于视频编码.
背景情况:
- 多功能视频编码 (VVC) 依赖于复杂的编码单元 (CU) 分区,以提高效率.
- 在VVC内部编码中,三元树 (TT) 分区是由于速率扭曲成本计算而计算密集的.
- 目前用于最佳CU分区选择的方法耗时,阻碍实时应用.
研究的目的:
- 为VVC的三元树 (TT) 分区在内部编码中开发一个快速决策机制.
- 为了减少与CU分区的速率扭曲优化 (RDO) 相关的计算复杂性.
- 为了提高整体的视频编码效率而不会损害视觉质量.
主要方法:
- 研究了图像结构特征和TT分区模式之间的相关性.
- 开发了一个高效的特征表示和提取方案,以最大限度地减少计算负载.
- 构建了全面的数据集,用于训练最佳TT分区选择的预测模型.
- 在VVC测试模型 (VTM) 中集成了一个预测模型,用于RDO前的特征分析.
主要成果:
- 拟议的机制有效地预测了最佳的TT分区模式,可以绕过复杂的RDO计算.
- 实验结果显示,与现有的轻量级神经网络算法相比,节省时间的显著改进.
- 该方法在预测准确性和模型复杂性之间实现了有利的权衡.
- 编码质量得到了维护,同时大幅加快了视频编码过程.
结论:
- 基于图像特征的决策机制为VVC内部编码提供了一个计算效率高的方法.
- 这种方法通过智能跳过不必要的TT分区计算,显著加速视频编码.
- 该方法在节省时间的指标和Bjøntegaard Delta Bit Rate (BDBR) 中表现出优异的性能,与之前的轻量级方法相比.
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