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Scalable wavelet video coding using aliasing-reduced hierarchical motion compensation

机译:使用减少混叠的分层运动补偿的可扩展小波视频编码

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摘要

We describe a spatially scalable video coding framework in which motion correspondences between successive video frames are exploited in the wavelet transform domain. The basic motivation for our coder is that motion fields are typically smooth and, therefore, can be efficiently captured through a multiresolutional framework. A wavelet decomposition is applied to each video frame and the coefficients at each level are predicted from the coarser level through backward motion compensation. To remove the aliasing effects caused by downsampling in the transform, a special interpolation filter is designed with the weighted aliasing energy as part of the optimization goal, and motion estimation is carried out with low pass filtering and interpolation in the estimation loop. Further, to achieve robust motion estimation against quantization noise, we propose a novel backward/forward hybrid motion compensation scheme, and a tree structured dynamic programming algorithm to optimize the backward/forward mode choices. A novel adaptive quantization scheme is applied to code the motion predicted residue wavelet coefficients, Experimental results reveal 0.3-2-dB increase in coded PSNR at low bit rates over the state-of-the-art H.263 standard with all enhancement modes enabled, and similar improvements over MPEG-2 at high bit rates, with a considerable improvement in subjective reconstruction quality, while simultaneously supporting a scalable representation.
机译:我们描述了一种空间可伸缩的视频编码框架,其中在小波变换域中利用了连续视频帧之间的运动对应关系。我们编码器的基本动机是运动场通常很平滑,因此可以通过多分辨率框架有效捕获。小波分解被应用于每个视频帧,并且通过向后运动补偿从较粗糙的级别预测每个级别的系数。为了消除变换中由于下采样引起的混叠效应,设计了一种特殊的插值滤波器,其中将加权的混叠能量作为优化目标的一部分,并且在估计循环中使用低通滤波和插值进行运动估计。此外,为了实现针对量化噪声的鲁棒运动估计,我们提出了一种新颖的后向/前向混合运动补偿方案,以及一种树状结构的动态规划算法来优化后向/前向模式选择。应用一种新颖的自适应量化方案对运动预测的残差小波系数进行编码,实验结果表明,在启用所有增强模式的情况下,与最新的H.263标准相比,低比特率下的编码PSNR增加了0.3-2-dB ,以及在高比特率下对MPEG-2的类似改进,在主观重建质量上有相当大的提高,同时还支持可伸缩的表示形式。

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