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Adaptive resynchronization approach for scalable video over wireless channel

机译:自适应重新同步方法,可通过无线通道进行可伸缩视频

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Scalable video coding technique is developed to provide a full scalability including temporal, spatial and quality scalability. The compressed bitstream can be separated into base layer and enhancement layers, where the base layer is usually small and of high importance. Error-free transmission could be realized for the base layer through high-priority protection. Therefore, the overall quality greatly depends on the enhancement layers. In this paper, we propose an adaptive resynchronization method to achieve a robust transmission of the enhancement layer information. The scheme firstly groups the enhancement layer bitstream of a group of pictures (GOPs) into a set of units with different temporal levels and quality levels. We measure the importance of each unit and organize them into hierarchical units from the most important unit to the least important one. The overall distortion is formulated and a local hill-climbing algorithm is designed to optimally insert different amount of resynchronization markers to different unit considering the time-varying channel conditions and the significance of each unit. It is shown from experimental results that the proposed method can perform a graceful degradation under a variety of error conditions and shows advantages over conventional method. The improvement is up to 1 dB. We also conduct the experiments to demonstrate that the resynchronization method can also be employed together with other error resilient methods to further improve the quality of the decoded video.
机译:开发了可伸缩视频编码技术以提供包括时间,空间和质量可伸缩性的完整可伸缩性。压缩后的比特流可以分为基础层和增强层,其中基础层通常很小并且非常重要。通过高优先级保护,可以实现基础层的无错传输。因此,总体质量很大程度上取决于增强层。在本文中,我们提出了一种自适应重新同步方法,以实现增强层信息的鲁棒传输。该方案首先将一组图片(GOP)的增强层比特流分组为具有不同时间水平和质量水平的一组单元。我们衡量每个单元的重要性,并将其从最重要的单元到最不重要的单元组织为分层单元。考虑到随时间变化的信道条件和每个单元的重要性,制定了整体失真并设计了局部爬山算法,以将不同数量的重新同步标记最佳地插入到不同单元中。从实验结果表明,所提出的方法可以在各种错误条件下进行适度的降级,并且显示出优于常规方法的优点。改善幅度高达1 dB。我们还进行了实验,以证明重新同步方法也可以与其他错误恢复方法一起使用,以进一步提高解码视频的质量。

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