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Efficient Intra and Most Probable Mode (MPM) Selection Based on Statistical Texture Features

机译:基于统计纹理特征的高效帧内和最可能的模式(MPM)选择

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High Efficiency video coding (HEVC) Encoder could give higher compression efficiency by offering 35 intra modes. However, this increases the complexity of the encoder due to more modes participate in the decision process. Therefore, it is necessary to build a fast and efficient intra prediction algorithm that is practical for real time application. Statistical properties of reference samples and the current intra block can be investigated to find out which modes will be efficient for the current block. Therefore, an adaptive and efficient modes selection model is presented in this paper. Firstly, intra modes are efficiently short listed by calculating the Euclidean distance between the statistical features of the reference samples and the current block. Secondly, an efficient MPM selection method is proposed that selects the modes for MPM by investigating the correlation between the neigh boring blocks and the current block. Experimental results demonstrate that average BD-Rate saving of the proposed approach is -0.11%, and BD-PSNR is improved by 0.0065%.
机译:高效视频编码(HEVC)编码器可以通过提供35个内部模式来提供更高的压缩效率。然而,由于更多模式参与决策过程,这增加了编码器的复杂性。因此,有必要建立一个快速高效的帧内预测算法,该算法实际应用实用。可以研究参考样本的统计特性和当前块的局部块,以了解电流块的效率将有效。因此,本文提出了一种自适应和有效的模式选择模型。首先,通过计算参考样本和当前块的统计特征之间的欧几里德距离来有效地列出了帧内模式。其次,提出了一种有效的MPM选择方法,其通过研究邻居钻头和当前块之间的相关性来选择MPM的模式。实验结果表明,该方法的平均BD速率储蓄为-0.11%,BD-PSNR提高0.0065%。

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