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A Multi-domain Motion Vectors Prediction Method for Spatial Scalability

机译:一种多域运动向量空间可伸缩性预测方法

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In scalable video coding, spatial scalability is a layered video representation with different spatial resolutions for the same video signal. Inter-layer motion information prediction is a method of improving coding performance for spatial scalability. In this paper, a multi-domain motion vectors prediction coding method for spatial scalability is proposed based on inter-layer motion information prediction. It consists of two spatial layers: one base layer and one enhancement layer. The proposed coding method is fully compatible with existing coding standard in base layer, while in enhancement layer a motion vector prediction mode is added. If this mode is selected, the motion vectors of temprol and spatial and inter-layer domain are exploited for motion vector prediction of current macroblock in enhancement layer. It will obtain a more accurate motion vector by using multi-domain motion vectors. The effectiveness of the new technique is demonstrated by simulation experimental results. With almost no changes on both computation complexity and encoded bitrate, the average increase of Y-PSNR is about 0.22 dB for sequence Foreman. and 0.17dB for Subway.
机译:在可伸缩视频编码中,空间可伸缩性是具有用于相同视频信号的不同空间分辨率的分层视频表示。层间运动信息预测是一种提高用于空间可伸缩性的编码性能的方法。本文提出了一种基于层间运动信息预测的用于空间可伸缩性的多域运动矢量预测编码方法。它由两个空间层组成:一个基层和一个增强层。所提出的编码方法与基础层中的现有编码标准完全兼容,而在增强层中添加了运动矢量预测模式。如果选择了这种模式,则针对增强层中当前宏块的运动矢量预测来利用TemproL和空间和层间域的运动向量。它将通过使用多域运动向量获得更准确的运动矢量。通过模拟实验结果证明了新技术的有效性。随着计算复杂性和编码比特率几乎没有变化,y-PSNR的平均增加为序列前部的0.22 dB。地铁0.17dB。

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