论文标题
HEVC中接近最佳的每张纸Lagangian乘数预测
Near Optimal Per-Clip Lagrangian Multiplier Prediction in HEVC
论文作者
论文摘要
大多数互联网流量是视频内容。这推动了对视频压缩的需求，以在低目标比特率下提供高质量的视频。已证明，针对特定视频剪辑（每盘优化）优化视频编解码器的参数可产生明显的比特率节省。在先前的工作中，我们已经表明，Lagrangian乘数的每盘倍数优化可提高24％的BD率改进。这些算法的关键组成部分是对适当的比特率范围内的R-D特性进行建模。这在计算上很重，因为它通常涉及不同参数设置的高分辨率材料的重复视频编码。这项工作着重于通过在较低的带宽功能上部署NN来减少这种计算负载。我们的系统在大约90％的大型语料库中实现了BD率的改进，与先前的直接优化工作相当。
The majority of internet traffic is video content. This drives the demand for video compression to deliver high quality video at low target bitrates. Optimising the parameters of a video codec for a specific video clip (per-clip optimisation) has been shown to yield significant bitrate savings. In previous work we have shown that per-clip optimisation of the Lagrangian multiplier leads to up to 24% BD-Rate improvement. A key component of these algorithms is modeling the R-D characteristic across the appropriate bitrate range. This is computationally heavy as it usually involves repeated video encodes of the high resolution material at different parameter settings. This work focuses on reducing this computational load by deploying a NN operating on lower bandwidth features. Our system achieves BD-Rate improvement in approximately 90% of a large corpus with comparable results to previous work in direct optimisation.
