扩展空间可扩展性中误差隐藏的有效残差预测

M. Shoaib, A. Cai
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引用次数: 4

摘要

本文研究了扩展空间可扩展性(ESS)中层间残差预测在隐藏丢失宏块(MB)和去除视觉伪影之间的权衡问题。为了改善视觉伪影,文献中提出了各种方案,包括在ESS增强层中对非匹配残差进行更高失真的残差预测。而在层间误差隐藏方法中,残差预测也用于隐藏丢失的mb。我们提出有效地利用残差预测来防止这些伪影以及隐藏丢失的mb,利用视频对象中同质特征的特征进行错误弹性编码。仿真结果表明,在JVT-V302规定的测试条件下,与JVT-W123相比,该方案在各种测试序列的解码器处获得了0.29 dB的PSNR增益,总体平均PSNR增益为0.1 dB。
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Efficient residual prediction with error concealment in extended spatial scalability
In this paper, inter-layer residual prediction's trade-off between concealing lost macroblock (MB) and removing visual artifact in extended spatial scalability (ESS) is investigated. In order to improve visual artifacts, various schemes are proposed in the literature, including higher distortion to the residual prediction used in ESS enhancement layer for non matching residuals. Whereas, residual prediction is also used to conceal lost MBs in inter-layer error concealment methods. We propose an efficient use of residual prediction to prevent those artifacts as well as to conceal lost MBs, exploiting features in homogenous characteristics in video objects for error resilient coding. Simulation results show that the proposed scheme achieves up to 0.29 dB PSNR gain, with overall average of 0.1 dB PSNR gain at the decoder for various tested sequences compared to JVT-W123 under testing conditions specified in JVT-V302.
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