Determining the best partitioning structure of a Coding Tree Unit (CTU) is one of the most time consuming operations in HEVC encoding. Specifically, it is the evaluation of the quadtree hierarchy using the Rate-Distortion (RD) optimization that has the most significant impact on the encoding time, especially in the cases of High Definition (HD) and Ultra High Definition (UHD) videos. In order to expedite the encoding for low delay applications, this paper proposes a Coding Unit (CU) size selection and encoding algorithm for inter-prediction in the HEVC. To this end, it describes (i) two CU classification models based on Inter N×N mode motion features and RD cost thresholds to predict the CU split decision, (ii) an online training scheme for dynamic content adaptation, (iii) a motion vector reuse mechanism to expedite the motion estimation process, and finally introduces (iv) a computational complexity to coding efficiency trade-off process to enable flexible control of the algorithm. The experimental results reveal that the proposed algorithm achieves a consistent average encoding time performance ranging from 55% - 58% and 57%-61% with average Bjøntegaard Delta Bit Rate (BDBR) increases of 1.93% –ud 2.26% and 2.14% – 2.33% compared to the HEVC 16.0 reference software for the low delay P and low delay B configurations, respectively, across a wide range of content types and bit rates.
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机译：确定编码树单元（CTU）的最佳分区结构是HEVC编码中最耗时的操作之一。特别是，使用速率失真（RD）优化对四叉树层次结构进行评估，对编码时间的影响最大，尤其是在高清（HD）和超高清（UHD）视频的情况下。为了加快低延迟应用的编码，本文提出了一种用于HEVC中的帧间预测的编码单元（CU）大小选择和编码算法。为此，它描述了（i）基于Inter N×N模式运动特征和RD成本阈值的两个CU分类模型，以预测CU分割决策；（ii）用于动态内容自适应的在线训练方案；（iii）运动向量重用机制以加快运动估计过程，最后将（iv）计算复杂度引入编码效率权衡过程，以实现对算法的灵活控制。实验结果表明，该算法实现了一致的平均编码时间性能，范围从55％-58％和57％-61％，平均BjøntegaardDelta比特率（BDBR）增加了1.93％– ud 2.26％和2.14％–与HEVC 16.0参考软件相比，在广泛的内容类型和比特率范围内，低延迟P和低延迟B配置分别为2.33％。
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