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Video Coding Mode Decision As a Classification Problem

机译:视频编码模式决定作为分类问题

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In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.
机译:在本文中,我们表明,基于新颖的机遇约束分类器,可以降低H.264 / AVC中的MB编码的复杂性。使用简单平均差值的对,我们的技术能够降低MB帧内编码过程的复杂性,在PSNR中的损失可忽略。我们提出了一种替代方法来解决相当于机器学习的分类问题。实施结果表明,该方法将编码时间减少到大约20%的参考实施,PSNR中的平均损耗为0.05 dB。

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