Analysis of packet loss for compressed video: Effect of burst losses and correlation between error frames
Analysis of packet loss for compressed video: Effect of burst losses and correlation between error frames
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DOI：
10.1109/tcsvt.2008.923139
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发表时间：
2008-07-01
影响因子：
8.4
通讯作者：
Girod, Bernd
中科院分区：
文献类型：
--
作者：
Liang, Yi J.;Apostolopoulos, John G.;Girod, Bernd
视频通信经常受到各种形式的丢失的困扰，例如Internet上的数据包丢失。本文研究了丢包模式，特别是突发长度对于准确估计压缩视频丢包导致的预期均方误差失真是否重要的问题。我们专注于低比特率视频的挑战性情况，其中每个p帧通常适合单个数据包。具体来说，我们：1)验证损耗模式确实对产生的失真有显著影响；2)解释为什么损耗模式，例如突发损耗，通常比相等数量的孤立损耗产生更大的失真；3)提出了一个能准确估计预期失真的模型。通过显式计算损耗模式、帧间错误传播和错误帧之间的相关性。用H.264/AVC编码视频和先前的帧隐藏验证了所提出模型的准确性，其中对于大多数序列，对于长度为两个数据包的突发损失，预测的总失真在+/- 0.3 dB以内，而之前的模型低估了约1.5 dB的失真。此外，随着爆发长度的增加，我们的预测在0.7 dB以内，而先前的模型会降低并低估超过3 dB的失真。该模型适用于低到中等运动的视频电话类型的序列。我们还提供了一个简单的说明性示例，说明如何使用突发损失影响的知识来适应视频流的时间表，以提高突发损失通道的性能，而不需要增加比特率。
Video communication is often afflicted by various forms of losses, such as packet loss over the Internet. This paper examines the question of whether the packet loss pattern, and in particular, the burst length, is important for accurately estimating the expected mean-squared error distortion resulting from packet loss of compressed video. We focus on, the challenging case of low-bit-rate video where each P-frame typically fits within a single packet. Specifically, we: 1) verify that the loss pattern does have a significant effect on the resulting distortion; 2) explain why a loss pattern, for example a burst loss, generally produces a larger distortion than an equal number of isolated losses; and 3) propose a model that accurately estimates the expected distortion. by explicitly accounting for the loss pattern, inter-frame error propagation, and the correlation between error frames. The accuracy of the proposed model is validated with H.264/AVC coded video and previous frame concealment, where for most sequences the total distortion is predicted to within +/- 0.3 dB for burst loss of length two packets, as compared to prior models which underestimate the distortion by about 1.5 dB. Furthermore, as the burst length increases, our prediction is within 0.7 dB, while prior models degrade and underestimate the distortion by over 3 dB. The proposed model works well for video-telephony-type of sequences with low to medium motion. We also present a simple illustrative example, of how knowledge of the effect of burst loss can be used to adapt the schedule of video streaming to provide improved performance for a burst loss channel, without requiring an increase in bit rate.