变换域DVC中支持向量机的全局和局部信息融合

Abdalbassir Abou-Elailah, F. Dufaux, J. Farah, Marco Cagnazzo
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引用次数: 5

摘要

侧信息对分布式视频编码的性能有很大的影响。通常,侧信息是使用运动补偿时间插值生成的。本文提出了一种基于支持向量机的全局和局部侧信息融合的新方法。全局侧信息在解码器处生成,使用在编码器处使用尺度不变特征变换估计的全局运动参数。实验结果表明,与参考DISCOVER编解码器相比,该方法在GOP大小为2时的PSNR提高了1.7 dB,在更大GOP大小时的PSNR提高了3.78 dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fusion of global and local side information using Support Vector Machine in transform-domain DVC
Side information has a strong impact on the performance of Distributed Video Coding. Commonly, side information is generated using motion compensated temporal interpolation. In this paper, we propose a new method for the fusion of global and local side information using Support Vector Machine. The global side information is generated at the decoder using global motion parameters estimated at the encoder using the Scale-Invariant Feature Transform. Experimental results show that the proposed approach can achieve a PSNR improvement of up to 1.7 dB for a GOP size of 2 and up to 3.78 dB for larger GOP sizes, with respect to the reference DISCOVER codec.
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