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Fast disparity estimation using spatio-temporal correlation of disparity field for multiview video coding

机译:多视点视频编码中使用视差场时空相关的快速视差估计

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Disparity estimation is adopted by multiview video coding (MVC) to reduce the inter-view redundancy. However, it consumes enormous computational load. In this paper, a fast disparity estimation is proposed by using the spatio-temporal correlation and the temporal variation of disparity field. For each macroblock, a temporal prediction of the disparity vector is calculated first by utilizing the smoothed disparity field of the previous coded frame. Then, the search center is selected among the candidates obtained from spatio-temporal neighboring disparity vectors, and deemed to be a preliminary disparity vector. Finally, the search range is predicted adaptively by using the distance between the search center and the temporal prediction of the disparity vector, and then the search is implemented in a limited range. The distance represents the temporal variation of the disparity vector. As compared to the full search algorithm in MVC reference software, experimental results show that an average 96% reduction of the computational complexity is achieved, while the rate-distortion performance remains the same. As compared to the fast search algorithm in MVC reference software, experimental results show that an average 43% reduction of the computational complexity is achieved, and the rate-distortion performance of the proposed algorithm has been improved.
机译:多视图视频编码(MVC)采用视差估计以减少视图间冗余。但是,它消耗了巨大的计算量。本文提出了一种利用时空相关性和视差场随时间变化的快速视差估计方法。对于每个宏块,首先通过利用先前编码帧的平滑视差字段来计算视差矢量的时间预测。然后,在从时空相邻视差矢量获得的候选中选择搜索中心,并将其视为初步视差矢量。最后,通过使用搜索中心与视差矢量的时间预测之间的距离来自适应地预测搜索范围,然后在有限范围内执行搜索。该距离表示视差矢量的时间变化。与MVC参考软件中的完全搜索算法相比,实验结果表明,计算复杂度平均降低了96%,而速率失真性能保持不变。与MVC参考软件中的快速搜索算法相比,实验结果表明,该算法的计算复杂度平均降低了43%,并且改进了算法的速率失真性能。

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