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Laplacian Mixture Model(LMM) based frame-layer rate control method for H.264/AVC high-definition video coding

机译:H.264 / AVC高清视频编码的基于拉普拉斯混合模型的帧层速率控制方法

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Accurate statistical distribution for estimating the transformed residues is greatly important for us to analyze the rate-distortion behavior of video encoders. However, the previous work pays more attention to those sequences of low-resolution. In this paper, we address the statistical characteristics of DCT coefficients of high-definition videos coded by H.264/AVC. The contribution of this paper is threefold: First, Laplacian Mixture Model (LMM) is proposed to model the residues instead of using Laplacian or Cauchy distributions; the corresponding new rate-distortion model based on LMM is presented next; based on this new rate-distortion model, one frame-layer rate control algorithm is developed. Experimental results showed that the proposed rate control method achieves an improvement of PSNR up to 0.52dB with less visual quality variation compared to JM 11.0.
机译:准确的统计分布对于估计转换后的残差非常重要,这对于我们分析视频编码器的速率失真行为非常重要。但是,先前的工作更加关注那些低分辨率序列。在本文中,我们解决了由H.264 / AVC编码的高清视频的DCT系数的统计特性。本文的贡献有三点:首先,提出了拉普拉斯混合模型(LMM)而不是使用拉普拉斯或柯西分布来对残渣进行建模。接下来给出相应的基于LMM的新的速率失真模型。基于这种新的速率失真模型,开发了一种帧层速率控制算法。实验结果表明,与JM 11.0相比,该速率控制方法可将PSNR提高到0.52dB,且视觉质量变化较小。

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