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Complexity-rate-distortion evaluation of video encoding for cloud media computing

机译:用于云媒体计算的视频编码的复杂度失真评估

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Cloud computing provides a promising solution to cope with the increased complexity in new video compression standards and the increased data volume in video source. It not only saves the cost of too frequent equipment upgrading but also gives individual users the flexibilities to choose the amount of computing according to their needs. To facilitate cloud computing for real-time video encoding, in this paper we evaluate the amount of computing resource needed for H.264 and H.264 SVC encoding. We focus on evaluating the complexity-rate-distortion (C-R-D) relationship with a fixed encoding process but under different external configuration parameters. We believe such an empirical study is meaningful for eventually realizing real-time video encoding in an optimal way in a cloud environment.
机译:云计算提供了一种有前途的解决方案,以应对新的视频压缩标准中日益增加的复杂性以及视频源中不断增长的数据量。它不仅节省了过于频繁的设备升级成本,而且还使个人用户可以根据自己的需求灵活地选择计算量。为了促进用于实时视频编码的云计算,在本文中,我们评估了H.264和H.264 SVC编码所需的计算资源量。我们专注于通过固定的编码过程但在不同的外部配置参数下评估复杂度-率-失真(C-R-D)关系。我们认为,这样的经验研究对于最终在云环境中以最佳方式最终实现实时视频编码是有意义的。

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