Bit-rate control using piecewise approximated rate-distortion characteristics
Bit-rate control using piecewise approximated rate-distortion characteristics
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DOI：
10.1109/76.709411
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发表时间：
1998-08
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通讯作者：
Liang-Jin Lin;Antonio Ortega
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作者：
Liang-Jin Lin;Antonio Ortega
数字视频的提高受欢迎程度在很大程度上是由一系列国际标准（MPEG-1，MPEG-2，H.263等）驱动的。在大多数标准中，速率控制方案在改善和稳定解码和播放质量方面起着重要作用，因此未定义，因此在每个编码器设计中都可以实施不同的策略。已经提出了几种基于费率的（R-D）基于给定的通道速率和缓冲尺寸的最佳质量的技术。这些方法很复杂，因为它们需要在做出量化分配决策之前要测量的输入数据的R-D特征。我们展示了如何在不显着降低优化过程的性能的情况下降低计算R-D数据的复杂性。我们提出了两种方法，可通过以下方式通过以下方式提供复杂性的连续降低，（1）使用模型来插值速率和失真特性，以及（2）使用过去的帧而不是当前框架来确定模型。我们的第一种方法适用于可能的情况（例如，广播视频），其中可能会有长时间的编码延迟，而我们的第二种方法对于计算受限的交互式视频应用程序更有用。第一种方法也可以用于基准其他方法。两种方法都可以超过1 dB峰值信号到噪声率（PSNR），例如MPEG测试模型5（TM5）速率控制，在场景变化过渡期间的增长更大。此外，这两种方法都是先验假设的，并且在视频源和编码率的范围内提供了鲁棒性。就复杂性而言，与更简单的技术相比，我们的第一种算法大约将编码时间加倍（例如TM5）。但是，与精确测量R-D数据的方法相比，复杂性大大降低。我们的第二个算法的复杂性略高于TM5，PSNR性能略低于第一种方法。
Digital video's increased popularity has been driven to a large extent by a flurry of international standards (MPEG-1, MPEG-2, H.263, etc). In most standards, the rate control scheme, which plays an important role in improving and stabilizing the decoding and playback quality, is not defined, and thus different strategies can be implemented in each encoder design. Several rate-distortion (R-D)-based techniques have been proposed aimed at the best possible quality for a given channel rate and buffer size. These approaches are complex because they require the R-D characteristics of the input data to be measured before making quantization assignment decisions. We show how the complexity of computing the R-D data can be reduced without significantly reducing the performance of the optimization procedure. We propose two methods which provide successive reductions in complexity by: (1) using models to interpolate the rate and distortion characteristics, and (2) using past frames instead of current ones to determine the models. Our first method is applicable to situations (e.g., broadcast video) where a long encoding delay is possible, while our second approach is more useful for computation-constrained interactive video applications. The first method can also be used to benchmark other approaches. Both methods can achieve over 1 dB peak signal-to-noise rate (PSNR) gain over simple methods like the MPEG Test Model 5 (TM5) rate control, with even greater gains during scene change transitions. In addition, both methods make few a priori assumptions and provide robustness in their performance over a range of video sources and encoding rates. In terms of complexity, our first algorithm roughly doubles the encoding time as compared to simpler techniques (such as TM5). However, the complexity is greatly reduced as compared to methods which exactly measure the R-D data. Our second algorithm has a complexity marginally higher than TM5 and a PSNR performance slightly lower than that of the first approach.