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Rate-Distortion-Optimized Video Transmission Using Pyramid Vector Quantization

机译:使用金字塔矢量量化的速率失真优化视频传输

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Conventional video compression relies on interframe prediction (motion estimation), intraframe prediction, and variable-length entropy encoding to achieve high compression ratios but, as a consequence, produces an encoded bit stream that is inherently sensitive to channel errors. In order to ensure reliable delivery over lossy channels, it is necessary to invoke various additional error detection and correction methods. In contrast, techniques such as pyramid vector quantization (PVQ) have the ability to prevent error propagation through the use of fixed-length codewords. This paper introduces an efficient rate-distortion optimization algorithm for intramode PVQ, which offers similar compression performance to intra H.264/AVC and Motion JPEG 2000, while offering inherent error resilience. The performance of our enhanced codec is evaluated for high-definition content in the context of a realistic (IEEE 802.11n) wireless environment with up to 11 dB PNR improvement over H.264/AVC. We show that PVQ provides greater tolerance to corrupted data while obviating the need for complex encoding tools.
机译:常规的视频压缩依赖于帧间预测(运动估计),帧内预测和可变长度熵编码来实现高压缩率,结果,产生的编码比特流本质上对信道错误敏感。为了确保在有损通道上的可靠传送,有必要调用各种其他的错误检测和纠正方法。相反,诸如金字塔矢量量化(PVQ)之类的技术具有通过使用固定长度码字来防止错误传播的能力。本文介绍了一种用于帧内模式PVQ的高效速率失真优化算法,该算法可提供与帧内H.264 / AVC和Motion JPEG 2000类似的压缩性能,同时提供固有的错误恢复能力。在现实的(IEEE 802.11n)无线环境中,针对高清内容评估了增强型编解码器的性能,与H.264 / AVC相比,PNR改善了11 dB。我们证明了PVQ可以更好地容忍损坏的数据,而无需使用复杂的编码工具。

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