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Generalized B pictures and the draft H.264/AVC video-compression standard

机译:广义的B图片和H.264 / AVC视频压缩标准草案

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This paper reviews recent advances in using B pictures in the context of the draft H.264/AVC video-compression standard. We focus on reference picture selection and linearly combined motion-compensated prediction signals. We show that bidirectional prediction exploits partially the efficiency of combined prediction signals whereas multihypothesis prediction allows a more general form of B pictures. The general concept of linearly combined prediction signals chosen from an arbitrary set of reference pictures improves the H.264/AVC test model TML-9 which is used in the following. We outline H.264/AVC macroblock prediction modes for B pictures, classify them into four groups and compare their efficiency in terms of rate-distortion performance. When investigating multihypothesis prediction, we show that bidirectional prediction is a special case of this concept. Multihypothesis prediction allows also two combined forward prediction signals. Experimental results show that this case is also advantageous in terms of compression efficiency. The draft H.264/AVC video-compression standard offers improved entropy coding by context-based adaptive binary arithmetic coding. Simulations show that the gains by multihypothesis prediction and arithmetic coding are additive. B pictures establish an enhancement layer and are predicted from reference pictures that are provided by the base layer. The quality of the base layer influences the rate-distortion trade-off for B pictures. We demonstrate how the quality of the B pictures should be reduced to improve the overall rate-distortion performance of the scalable representation.
机译:本文回顾了在H.264 / AVC视频压缩标准草案的背景下使用B图片的最新进展。我们专注于参考图片选择和线性组合的运动补偿预测信号。我们显示双向预测部分利用了组合预测信号的效率,而多假设预测则允许使用B图片的更通用形式。从任意参考图片集中选择的线性组合预测信号的一般概念改进了以下使用的H.264 / AVC测试模型TML-9。我们概述了B图片的H.264 / AVC宏块预测模式,将它们分为四类,并根据速率失真性能比较其效率。在研究多假设预测时,我们表明双向预测是该概念的特例。多假设预测还允许两个组合的前向预测信号。实验结果表明,这种情况在压缩效率方面也是有利的。 H.264 / AVC视频压缩标准草案通过基于上下文的自适应二进制算术编码提供了改进的熵编码。仿真表明,多假设预测和算术编码的增益是相加的。 B图片建立增强层,并根据基础层提供的参考图片进行预测。基本层的质量影响B图片的速率失真折衷。我们演示了如何降低B图片的质量,以提高可伸缩表示形式的整体速率失真性能。

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