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Adaptive DCT based depth map resampling for depth enhanced multiview video coding

机译:基于自适应DCT的深度图重采样,用于深度增强的多视图视频编码

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摘要

In this paper, we propose an adaptive downsampling pattern selection method for depth enhanced multiview video coding taking into account local characteristics of the depth map. The video content is divided into different stripes and a frequency-based measure is deployed to estimate the amount of degradation caused by downsampling and/or coding. The sampling pattern is determined for each vertical/horizontal stripe within a video in such a way that preserves the rectangular shape of the frames, hence the video sequence can be coded with any standard encoder. Simulation results show that the proposed method outperforms the reference by 0.18 dB of Bjontegaard delta Peak Signal-to-Noise Ratio (PSNR) or equivalently brings up to 22.56% and average of 9.84% of Bjontegaard delta bitrate reduction (dBR). It is also shown that the proposed algorithm reduces the complexity of the process to find a proper pattern to about 1% compared to the case where a full search is applied.
机译:在本文中,我们考虑到深度图的局部特征,提出了一种用于深度增强多视点视频编码的自适应下采样模式选择方法。视频内容被划分为不同的条带,并且采用基于频率的度量来估计由下采样和/或编码引起的降级量。为视频中的每个垂直/水平条纹确定采样模式的方式是保留帧的矩形形状,因此可以使用任何标准编码器对视频序列进行编码。仿真结果表明,所提出的方法比参考信号的Bjontegaard delta峰值信噪比(PSNR)高出0.18 dB,或者等效地达到了Bjontegaard delta比特率降低率(dBR)的22.56%和平均9.84%。还表明,与应用完全搜索的情况相比,所提出的算法将找到合适模式的过程的复杂性降低到大约1%。

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