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An optimally complexity scalable multi-mode decision algorithm for HEVC

机译:HEVC的最佳复杂度可扩展多模式决策算法

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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:HEVC中基于四叉树的编码单元结构以更大的计算复杂度为代价,提供了更多的运动补偿大小,以改善速率失真性能。与其他有关快速算法的研究不同,我们针对HEVC开发了最佳复杂度的可伸缩多模式决策算法(OCSMD)。本文有两个主要贡献。第一个是提出的新颖特征,用于描述MV场和CU深度之间的关系。第二个是,我们基于开销很小的特征且与标准没有冲突的功能,在帧级别上构建了性价比优先级预测模型。我们的方法可以在任意复杂度约束下,将计算资源分配给所有CU的帧级别的CU的MD,同时获得几乎最佳的编码性能。实验结果表明,我们的算法可以在变化的计算能力下调整复杂度,同时实现接近最佳的R-D性能。

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