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Correlation modeling with decoder-side quantization distortion estimation for distributed video coding

机译:分布式视频编码的解码器侧量化失真估计相关建模

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Aiming for low-complexity encoding, distributed video coders still fail to achieve the performance of current industrial standards for video coding. One of most important problems in this area is the accurate modeling of the correlation between the predicted signal and the original video. In our previous work we showed that exploiting the quantization distortion can significantly improve the accuracy of a correlation estimator. In this paper we describe how the quantization distortion can be exploited purely at the decoder side without any performance penalty when compared to an encoder-aided system. As a result, the proposed correlation estimator delivers state-of-the-art modeling accuracy while neatly fitting the low-encoder-complexity characteristic of distributed video coding.
机译:瞄准低复杂度编码,分布式视频编码器仍无法达到当前视频编码工业标准的性能。该领域中最重要的问题之一是对预测信号和原始视频之间的相关性进行精确建模。在我们以前的工作中,我们证明了利用量化失真可以显着提高相关估计器的准确性。在本文中,我们描述了与编码器辅助系统相比,如何在解码器端完全利用量化失真而不会造成任何性能损失。结果,所提出的相关估计器提供了最先进的建模精度,同时又很好地拟合了分布式视频编码的低编码器复杂度特性。

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