Rate-Distortion Optimization Using Adaptive Lagrange Multipliers
Rate-Distortion Optimization Using Adaptive Lagrange Multipliers
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DOI：
10.1109/tcsvt.2018.2873837
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发表时间：
2019-10
影响因子：
8.4
通讯作者：
Fan Zhang;D. Bull
中科院分区：
文献类型：
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作者：
Fan Zhang;D. Bull
在目前标准化的混合视频编码器中，拉格朗日乘子确定模型是率失真优化的关键组成部分。它起源于大约20年前，基于熵约束的高速率近似和使用H.263参考编码器在有限的测试材料上获得的实验结果。在本文中，我们全面分析了使用H.264/AVC和HEVC参考编码器对各种视频内容进行拉格朗日乘子选择实验的结果。这些结果表明，在这两种视频编码器中使用的原始拉格朗日乘子选择方法能够在I帧和P帧中获得最佳的率失真性能，但在B帧中表现不佳。确定了B帧的最佳拉格朗日乘子与实验结果得到的失真信息之间的关系，提出了一种新的拉格朗日乘子确定方法。该方法基于最近重构帧的失真统计，自适应预测B帧的最优拉格朗日乘子。将该方法集成到H.264/AVC和HEVC参考编码器中，在36个不同分辨率和不同内容类型的测试序列上进行了评估。结果表明，在最小的额外复杂性下，各种分层B帧配置可以节省一致的比特率。当对所有帧使用恒定量化参数（QP）值时，BD平均节省约3%，当对不同的B帧分层级别使用非零QP偏移值时，BD节省约0.5%。
In current standardized hybrid video encoders, the Lagrange multiplier determination model is a key component in rate-distortion optimization. This originated some 20 years ago based on an entropy-constrained high-rate approximation and experimental results obtained using an H.263 reference encoder on limited test material. In this paper, we present a comprehensive analysis of the results of a Lagrange multiplier selection experiment conducted on various video content using H.264/AVC and HEVC reference encoders. These results show that the original Lagrange multiplier selection methods, employed in both video encoders, are able to achieve optimum rate-distortion performance for I and P frames, but fail to perform well for B frames. The relationship is identified between the optimum Lagrange multipliers for B frames and distortion information obtained from the experimental results, leading to a novel Lagrange multiplier determination approach. The proposed method adaptively predicts the optimum Lagrange multiplier for B frames based on the distortion statistics of recent reconstructed frames. After integration into both H.264/AVC and HEVC reference encoders, this approach was evaluated on 36 test sequences with various resolutions and differing content types. The results show consistent bitrate savings for various hierarchical B frame configurations with minimal additional complexity. BD savings average approximately 3% when constant quantization parameter (QP) values are used for all frames, and 0.5% when non-zero QP offset values are employed for different B frame hierarchical levels.