Mode Duplication Based Multiview Multiple Description Video Coding

Xiaolan Wang, C. Cai
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引用次数: 5

Abstract

Compression ability is most concerned for multiview video (MVV) transmission system because of its massive amount of data. To improve coding efficiency, the Joint Video Team (JVT) standardization body has developed a joint multiview video coding model (JMVC), in which both intra-view and inter-view prediction techniques are exploited to yield a better coding gain. Therefore, how to prevent from error propagation has become a critical issue in multiview video coding (MVC). Error concealment methods for MVC have been widely studied in recent years, but little research has been conducted on error resilience for MVC. Multiple description coding (MDC) provides a promising solution for robust data transmission over error-prone channels, and has found many applications in monoview video communications. However, these MDC frameworks are not applicable to MVC because its prediction structure involves inter-view prediction. To develop an efficient and robust MVC scheme, a novel MDC algorithm for JMVC based on the mode duplication strategy is proposed in this paper. The input MVV sequence is firstly sub sampled in both horizontal and vertical directions, forming four subsequences, X1p, X1d, X2p, and X2d. Then, X1p and X1d are paired to form description 1, and X2p and X2d are grouped to form description 2, respectively. Secondly, X1p and X2p are directly encoded by separate JMVC encoders. Meanwhile, X1d/X2d adopts the best modes and prediction vectors (PVs) of X1p/X2p in corresponding (same spatial) locations to perform prediction coding. Consequently, neither code for best modes and PVs nor time load for mode decision is needed while coding X1d and X2d. Only coding for the prediction errors is required. Because subsequences in the same description are closely resembled each other, the extra prediction errors introduced by this best mode and PV reuse are negligible. Therefore, the bit rate and computational cost for coding X1d and X2d are greatly reduced. The proposed algorithm has been integrated into JMVC 6.0 and experimented on multiple MVV test sequences. The experimental results have shown that the proposed algorithm outperforms the state-of-the-arts of MDC for MVV and stereoscopic video, achieving improvements of 0.5-3dB in central decode and 0.5-3.5dB in side decode at the same bit rate over a wide range from 500kbps to 6000kbps. Comparing with original JMVC, the proposed algorithm saves about 40% encoding time in average.
基于模式复制的多视图多描述视频编码
由于多视场视频传输系统的数据量巨大,压缩能力成为多视场视频传输系统中最受关注的问题。为了提高编码效率,联合视频小组(JVT)标准化机构开发了一种联合多视点视频编码模型(JMVC),该模型利用视点内和视点间预测技术来获得更好的编码增益。因此,如何防止错误传播成为多视图视频编码(MVC)中的一个关键问题。近年来,对MVC的错误隐藏方法进行了广泛的研究,但对MVC的错误恢复能力的研究却很少。多描述编码(multi - description coding, MDC)为在易出错的信道上实现健壮的数据传输提供了一种很有前途的解决方案,并在单视图视频通信中得到了许多应用。然而,这些MDC框架并不适用于MVC,因为它的预测结构涉及到视图间预测。为了开发一种高效、鲁棒的MVC模式,本文提出了一种基于模式复制策略的JMVC多MDC算法。输入MVV序列首先在水平方向和垂直方向上进行子采样,形成X1p、X1d、X2p和X2d四个子序列。然后,将X1p和X1d配对形成描述1,将X2p和X2d分组形成描述2。其次,X1p和X2p由单独的JMVC编码器直接编码。同时,X1d/X2d采用X1p/X2p在对应(相同空间)位置的最佳模式和预测向量(pv)进行预测编码。因此,在编码X1d和X2d时,既不需要最佳模式和pv的代码,也不需要模式决策的时间负载。只需要对预测误差进行编码。由于同一描述中的子序列彼此非常相似,因此该最佳模式和PV重用引入的额外预测误差可以忽略不计。因此,大大降低了编码X1d和X2d的比特率和计算成本。该算法已集成到JMVC 6.0中,并在多个MVV测试序列上进行了实验。实验结果表明,该算法在MVV和立体视频中优于最先进的MDC,在500kbps到6000kbps的宽范围内,在相同的比特率下,中央解码提高了0.5-3dB,侧解码提高了0.5-3.5dB。与原有的JMVC算法相比,该算法平均节省约40%的编码时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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