基于快速二维经验模态分解和希尔伯特变换的视频振动测量研究

Honglei Du, Z. Zhong
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引用次数: 0

摘要

针对基于视频相位的振动测量算法抗噪性差的问题,提出了一种基于增强快速经验模态分解和Hilbert相位运动估计(EFEMD-HPME)的算法。EFEMD将多分量视频图像分解为单分量图像,然后通过Hilbert变换提取单分量图像的局部相位信息,与带通滤波器的频谱分解技术相比,该方法具有更好的抗噪性。实验表明,与HPME相比,本文算法的信噪比提高了30%左右,相对误差小于0.5%,这对于提高一般测量环境下视频振动测量的鲁棒性具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on video vibration measurement based on fast two-dimensional empirical mode decomposition and Hilbert transform
Against the poor noise immunity of the vibration measurement algorithm based on video phase, this paper proposes an algorithm based on enhanced fast empirical mode decomposition and Hilbert phase-based motion estimation (EFEMD-HPME). EFEMD decomposes the multicomponent video image into a single-component image, and then the local phase information of single component image is extracted through Hilbert transform, which has superior noise immunity compared with the spectral decomposition technique of the band-pass filter. Experiments show that the algorithm proposed in this article has a signal-to-noise ratio improvement of about 30% and a relative error of less than 0.5% compared with the HPME, which is of great significance for improving the robustness of video vibration measurement in general measurement environments.
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