GOP-Level Transmission Distortion Modeling for Video Streaming over Mobile Networks

Yu Han, Aidong Men, Kan Chang, Ziyi Quan
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引用次数: 2

Abstract

A major challenge in video coding and transmission over mobile networks is that the wireless channel is error-prone and the channel resources are limited. In this work, we analyze the picture distortion caused by channel errors and the distortion propagation behavior in its subsequent frames along the motion prediction path. We propose a linear fitting approach algorithm to achieve a low complexity GOP-level transmission distortion modeling. It is a predictive modeling which allows the encoder to predict the transmission distortion before the whole GOP is compressed and transmitted. The simulation results demonstrate that the proposed modeling has low computational complexity and high accuracy. It can be used in allocating the limited channel resources optimally for mobile video applications.
移动网络视频流的gop级传输失真建模
在移动网络上进行视频编码和传输的一个主要挑战是无线信道容易出错和信道资源有限。在这项工作中,我们分析了由信道误差引起的图像失真以及沿运动预测路径在其后续帧中的失真传播行为。我们提出了一种线性拟合算法来实现低复杂度的gop级传输失真建模。它是一种预测模型,允许编码器在整个GOP压缩和传输之前预测传输失真。仿真结果表明,该模型计算复杂度低,精度高。它可以用于对移动视频应用中有限的信道资源进行优化分配。
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