Real-Time Video Streaming Using Randomized Expanding Reed–Solomon Code
Real-Time Video Streaming Using Randomized Expanding Reed–Solomon Code
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DOI：
10.1109/tcsvt.2013.2248235
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发表时间：
2013-11
影响因子：
8.4
通讯作者：
Jimin Xiao;T. Tillo;Yao Zhao
中科院分区：
文献类型：
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作者：
Jimin Xiao;T. Tillo;Yao Zhao
前向纠错（FEC）码被广泛研究以在不可靠网络上保护流视频。通常，增大FEC编码块大小可以提高纠错性能。对于视频流应用，这可以通过将多于一个视频帧分组到一个FEC编码块中来实现。然而，在这种情况下，它会导致解码延迟，这对于实时视频流应用是不可容忍的。针对这一问题，提出了一种基于随机扩展RS码的实时视频流传输方案。在该方案中，RS编码块不仅包括当前帧的视频分组，而且还可以包括当前图片组中的先前帧的所有视频分组。在解码侧，当前帧的奇偶校验方程与先前帧的所有奇偶校验方程联合求解。由于后续帧的视频包不包含在RS编码块中，因此在编码侧和解码侧都不会引起等待后续帧的视频包或奇偶校验包的延迟。实验结果表明，该方案的性能明显优于其他实时容错视频流方法，特别是对于Foreman序列，该方案在10%i.i.d.分组丢失率，而对于突发丢失情况，平均增益大于3dB。本文的MATLAB代码可在http://www.mmtlab.com下载。
Forward error correction (FEC) codes are widely studied to protect streamed video over unreliable networks. Typically, enlarging the FEC coding block size can improve the error correction performance. For video streaming applications, this could be implemented by grouping more than one video frame into one FEC coding block. However, in this case, it leads to decoding delay, which is not tolerable for real-time video streaming applications. In this paper, to solve this dilemma, a real-time video streaming scheme using randomized expanding Reed-Solomon (RS) code is proposed. In this scheme, the RS coding block includes not only the video packets of the current frame, but could also include all the video packets of previous frames in the current group of pictures. At the decoding side, the parity-check equations of the current frame are jointly solved with all the parity-check equations of the previous frames. Since video packets of the following frames are not encompassed in the RS coding block, no delay will be caused for waiting for the video or parity packets of the following frames both at encoding and decoding sides. Experimental results show that the proposed scheme outperforms other real-time error resilient video streaming approaches significantly, specifically, for the Foreman sequence, the proposed scheme could provide 1.5 dB average gain over the state-of-the-art approach for 10% i.i.d. packet loss rate, whereas for the burst loss case, the average gain is more than 3 dB.MATLAB code of this paper is available for download at http://www.mmtlab.com.