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The Study on Decision Tree Classification and Three-Step Search Algorithm Based Compression Technology for High Efficiency Video Coding

机译:基于决策树分类的研究和基于三步搜索算法的高效视频编码的压缩技术

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The new generation video coding algorithm HEVC reduces the bitrate by half compared to the previous standard H.264 with the same video quality, but this also brings the increasing of encoding time. In this paper, we mainly improve the intra frame prediction to solve this question: Combined with the decision tree method in machine learning, the reference pixel smoothing characteristics of the prediction unit of each partition mode are quickly determined, and some intra modes with the same prediction result are adaptively skipped, which greatly saves coding time. Experimental results show that the proposed decision tree and three-step search based intra prediction algorithm achieves better performance compared with the HM15.0 encoder. The BD-Rate is increased by 1.19%, the BD-PSNR is decreased by 0.058dB, and the encoding time is reduced by 37.87% on average.
机译:新一代视频编码算法HEVC与具有相同视频质量的先前标准的H.264相比,将比特率降低一半,但这也带来了增加的编码时间。在本文中,我们主要提高帧内帧内预测来解决这个问题:结合决策树方法在机器学习中,每次分区模式的预测单元的参考像素平滑特性快速确定,并且一些具有相同的帧内模式预测结果是自适应跳过的,这大大节省了编码时间。实验结果表明,与HM15.0编码器相比,所提出的决策树和三步搜索的帧内预测算法实现了更好的性能。 BD速率提高1.19%,BD-PSNR降低0.058dB,平均编码时间减少了37.87%。

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