基于SVM的高效HEVC内部预测

Jia-Kai Liu, Yinyi Lin
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引用次数: 1

摘要

本文提出了一种基于支持向量机(SVM)的快速高效的模式间预测方法。在该算法中,我们使用MV方差、相邻CU深度等级和编码块标志(CBF)等信息作为基于支持向量机的CU大小决策的特征;MV方差、SKIP标志和RDO比值用于基于svm的PU模式判定。实验结果表明,该算法在比特率仅增加0.09%的情况下,与原HEVC互预测算法相比,计算时间平均减少29.6%。
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Efficient HEVC Inter Prediction using SVM
In this paper, we propose a fast and efficient inter mode decision using support vector machine (SVM) for HEVC inter prediction. In the proposed algorithm, we use information such as MV variance, neighboring CU depth level and coded block flag (CBF) as features for SVM-based CU size decision; while MV variance, SKIP flag and RDO ratio for SVM-based PU mode decision. The experimental results reveal that the proposed algorithm can achieve average 29.6% reduction of computation time with 0.09% bit rate increment only, compared to the original HEVC inter prediction.
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