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AN OPTIMALLY COMPLEXITY SCALABLE MULTI-MODE DECISION ALGORITHM FOR HEVC

机译:HEVC的最佳复杂性可伸缩多模式决策算法

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Quad-tree based Coding Unit structure in HEVC provides more motion compensation sizes to improve rate-distortion performance at the cost of greatly increased computational complexity. Different from other researches on fast algorithms, we develop an optimally complexity scalable multi-mode decision algorithm (OCSMD) for HEVC. There are two major contributions in this paper. The first one is a novel feature proposed to describe the relationship between MV field and CU depth. The second is that we build a cost-performance priority predicting model in frame level based on the feature with negligible overhead as well as no conflict with the standard. Our method may allocate computational resources to the MD of all the CUs in frame level under arbitrary complexity constraints, while obtaining nearly optimal coding performance. The experimental result shows that our algorithm can adjust complexity under varying computing capacity while achieving near-optimal R-D performance.
机译:基于四树的编码单元结构在HEVC提供了更多的运动补偿尺寸,以提高率变形性能,以大大提高计算复杂性。与快速算法的其他研究不同,我们为HEVC开发了最佳的复杂性可扩展多模式决策算法(OCSMD)。本文有两种主要贡献。第一个是一种新颖的特征,提出描述MV场和Cu深度之间的关系。第二个是,我们基于具有可忽略的特征的特征来构建帧级别的成本性能优先预测模型,也可以忽略不计,并且与标准没有冲突。我们的方法可以在任意复杂性约束下将计算资源分配给帧级别的所有CU的MD,同时获得几乎最佳的编码性能。实验结果表明,我们的算法可以在不同的计算能力下调整复杂性,同时实现近最佳的R-D性能。

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