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

机译:云媒体计算视频编码的复杂性 - 速率畸变评估

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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:云计算提供了有希望的解决方案,以应对新的视频压缩标准中的复杂性增加以及视频源中的增加的数据量。它不仅可以节省太频繁的设备升级的成本,而且还提供了个人用户根据其需求选择计算量的灵活性。为了便于云计算进行实时视频编码,在本文中,我们评估H.264和H.264 SVC编码所需的计算资源量。我们专注于评估复杂性率 - 失真(C-R-D)关系,而是根据不同的外部配置参数。我们相信这样一个实证研究对于最终实现在云环境中最佳方式的实时视频编码是有意义的。

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