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基于总体经验模态分解算法的光学条纹图案自适应分析

Adaptive analysis of optical fringe patterns using ensemble empirical mode decomposition algorithm.

作者信息

Zhou Xiang, Zhao Hong, Jiang Tao

机构信息

State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.

出版信息

Opt Lett. 2009 Jul 1;34(13):2033-5. doi: 10.1364/ol.34.002033.

Abstract

An approach based on a novel technique, called ensemble empirical mode decomposition, is proposed to adaptively reduce noise and remove background intensity from a two-dimensional fringe pattern. It can solve the mode-mixing problem of the original empirical mode decomposition caused by the existence of intermittent noise in fringe signals. Then a strategy is developed to automatically identify and group the resulting intrinsic mode functions for the purpose of eliminating noise and background of the fringe pattern. This approach is applied to process the simulated and practical fringe patterns, compared with Fourier transform and wavelet methods.

摘要

提出了一种基于一种名为总体经验模态分解的新技术的方法,以自适应地降低噪声并从二维条纹图案中去除背景强度。它可以解决由于条纹信号中存在间歇性噪声而导致的原始经验模态分解的模态混叠问题。然后开发了一种策略,用于自动识别和分组所得的固有模态函数,以消除条纹图案的噪声和背景。将该方法应用于处理模拟和实际条纹图案,并与傅里叶变换和小波方法进行比较。

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