A framework for efficient progressive fine granularity scalable video coding
A framework for efficient progressive fine granularity scalable video coding
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DOI：
10.1109/76.911159
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发表时间：
2001-03
期刊：
影响因子：
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通讯作者：
Feng Wu;Shipeng Li;Ya-Qin Zhang
中科院分区：
文献类型：
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作者：
Feng Wu;Shipeng Li;Ya-Qin Zhang
提出了一种有效的可伸缩视频编码的基本框架，即渐进细粒度可伸缩（PFGS）视频编码。与MPEG-4中的精细粒度可伸缩（PGS）视频编码类似，PFGS框架具有精细粒度比特率可伸缩性、信道自适应和错误恢复等精细粒度可伸缩视频编码的所有特性。另一方面，与PGS编码不同，PFGS框架使用具有增加的质量的多层参考，以使运动预测更准确，从而提高视频编码效率。然而，使用具有不同质量的多层引用也会引入一些问题。首先，需要额外的帧缓冲器来存储多个重构的参考层。这将增加PFGS方案的存储器成本和计算复杂度。在基本框架的基础上，进一步提出了一个简化高效的PFGS框架。简化的PPGS框架只需要一个额外的帧缓冲区，几乎相同的编码效率，在原来的框架。其次，当从低质量参考切换到高质量参考时，可能存在待编码系数的不期望的增加和波动，这可能部分地抵消使用高质量参考的优点。进一步改进的PFGS方案可以通过始终对所有增强层仅使用一个高质量预测参考来消除切换参考时增强层系数的波动。实验结果表明，PFGS框架可以提高编码效率超过1 dB的FGS方案的平均PSNR，但仍然保持所有的原始属性，如细粒度，带宽自适应，和错误恢复。一个简单的模拟传输PFGS视频在无线信道上进一步证实了PFGS方案的错误鲁棒性，虽然PFGS的优点还没有得到充分利用。
A basic framework for efficient scalable video coding, namely progressive fine granularity scalable (PFGS) video coding is proposed. Similar to the fine granularity scalable (PGS) video coding in MPEG-4, the PFGS framework has all the features of FGS, such as fine granularity bit-rate scalability, channel adaptation, and error recovery. On the other hand, different from the PGS coding, the PFGS framework uses multiple layers of references with increasing quality to make motion prediction more accurate for improved video-coding efficiency. However, using multiple layers of references with different quality also introduces several issues. First, extra frame buffers are needed for storing the multiple reconstructed reference layers. This would increase the memory cost and computational complexity of the PFGS scheme. Based on the basic framework, a simplified and efficient PFGS framework is further proposed. The simplified PPGS framework needs only one extra frame buffer with almost the same coding efficiency as in the original framework. Second, there might be undesirable increase and fluctuation of the coefficients to be coded when switching from a low-quality reference to a high-quality one, which could partially offset the advantage of using a high-quality reference. A further improved PFGS scheme can eliminate the fluctuation of enhancement-layer coefficients when switching references by always using only one high-quality prediction reference for all enhancement layers. Experimental results show that the PFGS framework can improve the coding efficiency up to more than 1 dB over the FGS scheme in terms of average PSNR, yet still keeps all the original properties, such as fine granularity, bandwidth adaptation, and error recovery. A simple simulation of transmitting the PFGS video over a wireless channel further confirms the error robustness of the PFGS scheme, although the advantages of PFGS have not been fully exploited.