Amplitude-Based Filtering for Video Magnification in Presence of Large Motion
Amplitude-Based Filtering for Video Magnification in Presence of Large Motion
复制标题
存在大运动时用于视频放大的基于幅度的滤波
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Zhao Yang
中科院分区：
文献类型：
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作者：
Xiu Wu;Xuezhi Yang;Jing Jin;Zhao Yang
视频放大揭示了世界上重要的、信息量丰富的细微变化。当使用传统的视频放大方法时，这些信号经常与导致显著模糊伪影和光晕的大运动相结合。针对这些问题，本文提出了一种基于幅度的滤波算法，该算法能够在存在大运动的情况下放大视频中的微小变化。我们试图了解小变化和大运动的幅度特征，目的是提取准确的信号用于可视化。基于频谱幅度滤波，欧拉方法可以在去除大运动的同时放大小的变化。该算法的一个优点是它可以处理大型运动，无论它们是线性的还是非线性的。我们的实验结果表明，该方法可以在存在大运动的情况下放大细微变化，并显著减少伪影。通过与现有算法的比较，验证了该算法的有效性，并为该算法提供了主客观证据。
Video magnification reveals important and informative subtle variations in the world. These signals are often combined with large motions which result in significant blurring artifacts and haloes when conventional video magnification approaches are used. To counter these issues, this paper presents an amplitude-based filtering algorithm that can magnify small changes in video in presence of large motions. We seek to understand the amplitude characteristic of small changes and large motions with the goal of extracting accurate signals for visualization. Based on spectrum amplitude filtering, the large motions can be removed while small changes can still be magnified by Eulerian approach. An advantage of this algorithm is that it can handle large motions, whether they are linear or nonlinear. Our experimental results show that the proposed method can amplify subtle variations in the presence of large motion, as well as significantly reduce artifacts. We demonstrate the presented algorithm by comparing to the state-of-the-art and provide subjective and objective evidence for the proposed method.