基于傅里叶变换的电子散斑干涉信息提取方法研究及应用
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摘要
电子散斑干涉(ESPI)测量技术是一种无损的全场光学测量技术,被广泛地应用于光学粗糙表面位移、变形测量、无损检测和振动分析领域。高精度地提取电子散斑干涉信息是应用ESPI技术的关键。本文针对基于傅里叶变换的电子散斑干涉信息提取方法进行了研究。
本文的主要研究内容有:(1)提出计算ESPI条纹方向的傅里叶变换方法,并与梯度法、累积平方差法进行比较。(2)提出计算ESPI条纹密度的傅里叶变换方法。条纹的方向和密度作为电子散斑干涉图像的基本信息,不仅是本文的一个重点,更有指导图像其它处理的重要作用。尤其是条纹方向,其精确性直接影响着处理效果。(3)根据ESPI条纹的方向和密度设计方向滤波器和密度滤波器,并将滤波器与图像的频率相乘,实现在频域内图像滤波。方向滤波器的带宽及其通带特性根据局部范围内条纹方向的一致程度来设定。密度滤波器采用简单的2维2阶巴特沃斯带通滤波器来实现对噪声的限制。方向滤波器和密度滤波器的组合对散斑噪声进行了有效的滤除。同时,本文加入根滤波和阈值处理的思想,有效地改善了滤波结果。(4)将本文的滤波方法应用于计算机模拟的和实验获得的ESPI条纹图、相位图滤波处理中,并与已发表的基于傅里叶变换的其它方法进行了比较。实验结果展示了本文提出的电子散斑干涉信息提取方法的性能。
基于傅里叶变换的ESPI信息提取方法具有以下几个优点:(1)算法简单、适用性强,可以应用在高密度、强噪声、低质量的图像中;(2)算法参数少,易调试。(3)可以计算条纹的方向和密度。
The Electronic Speckle Pattern Interferometry (ESPI) is a non-destructive, whole-field optical measurement technique, which is applied widely in optical rough surface displacement measurement, strain analysis, non-destructive technology (NDT) and vibration measurement. Therefore, the key of ESPI application is to extract information of ESPI correctly. In this paper, we make a research on the method of extracting information of ESPI based on the Fourier Transform (FT).
The primary coverage of this paper includes four parts: (1) A method based on FT is proposed to estimate the orientation of ESPI, which is compared with the Gradient based Method and Accumulate Differences Method. (2) We proposed a method to calculate the frequency of ESPI based on FT. As the basic information of ESPI, orientation and frequency are not only the emphasis of the paper, but also can direct fringe image processing. In particular, the direction affects the accuracy of the fringe analysis critically. (3) The angular filter and the density filter are derived by the angle and density of the speckle fringes. And then the noise reduction achieved by multiplying the FT of the image by the two filters. We utilize orientation coherence measure to adapt the angular bandwidth and characteristic of the directional filter. Density filter is a simple 2D band-pass Butterworth filter, which used to reduce noise. Combining these two filters can suppress noise effectively. The proposed filters have better result when adding root filtering and threshold. (4) We experimentally compare the proposed approach to other filtering approaches based on FT in literature via application to a variety of test cases, which are obtained by computer simulation or experiment. The experimental results show that our technique performs favorably and has high practical value.
Three advantages are mentioned about extraction information of ESPI based on FT. Firstly, the algorithm keep simple and applicative, and is proved effective for most of the patterns, especially for dense poor quality patterns. Secondly, it’s convenient to make use of the algorithm since there’s only two variable: window size and the threshold. Thirdly it can estimate the intrinsic properties of the patterns such as the local ridge orientation and local ridge frequency.
本文的主要研究内容有:(1)提出计算ESPI条纹方向的傅里叶变换方法,并与梯度法、累积平方差法进行比较。(2)提出计算ESPI条纹密度的傅里叶变换方法。条纹的方向和密度作为电子散斑干涉图像的基本信息,不仅是本文的一个重点,更有指导图像其它处理的重要作用。尤其是条纹方向,其精确性直接影响着处理效果。(3)根据ESPI条纹的方向和密度设计方向滤波器和密度滤波器,并将滤波器与图像的频率相乘,实现在频域内图像滤波。方向滤波器的带宽及其通带特性根据局部范围内条纹方向的一致程度来设定。密度滤波器采用简单的2维2阶巴特沃斯带通滤波器来实现对噪声的限制。方向滤波器和密度滤波器的组合对散斑噪声进行了有效的滤除。同时,本文加入根滤波和阈值处理的思想,有效地改善了滤波结果。(4)将本文的滤波方法应用于计算机模拟的和实验获得的ESPI条纹图、相位图滤波处理中,并与已发表的基于傅里叶变换的其它方法进行了比较。实验结果展示了本文提出的电子散斑干涉信息提取方法的性能。
基于傅里叶变换的ESPI信息提取方法具有以下几个优点:(1)算法简单、适用性强,可以应用在高密度、强噪声、低质量的图像中;(2)算法参数少,易调试。(3)可以计算条纹的方向和密度。
The Electronic Speckle Pattern Interferometry (ESPI) is a non-destructive, whole-field optical measurement technique, which is applied widely in optical rough surface displacement measurement, strain analysis, non-destructive technology (NDT) and vibration measurement. Therefore, the key of ESPI application is to extract information of ESPI correctly. In this paper, we make a research on the method of extracting information of ESPI based on the Fourier Transform (FT).
The primary coverage of this paper includes four parts: (1) A method based on FT is proposed to estimate the orientation of ESPI, which is compared with the Gradient based Method and Accumulate Differences Method. (2) We proposed a method to calculate the frequency of ESPI based on FT. As the basic information of ESPI, orientation and frequency are not only the emphasis of the paper, but also can direct fringe image processing. In particular, the direction affects the accuracy of the fringe analysis critically. (3) The angular filter and the density filter are derived by the angle and density of the speckle fringes. And then the noise reduction achieved by multiplying the FT of the image by the two filters. We utilize orientation coherence measure to adapt the angular bandwidth and characteristic of the directional filter. Density filter is a simple 2D band-pass Butterworth filter, which used to reduce noise. Combining these two filters can suppress noise effectively. The proposed filters have better result when adding root filtering and threshold. (4) We experimentally compare the proposed approach to other filtering approaches based on FT in literature via application to a variety of test cases, which are obtained by computer simulation or experiment. The experimental results show that our technique performs favorably and has high practical value.
Three advantages are mentioned about extraction information of ESPI based on FT. Firstly, the algorithm keep simple and applicative, and is proved effective for most of the patterns, especially for dense poor quality patterns. Secondly, it’s convenient to make use of the algorithm since there’s only two variable: window size and the threshold. Thirdly it can estimate the intrinsic properties of the patterns such as the local ridge orientation and local ridge frequency.
引文
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[2]唐晨,任宏伟,陈霞等,电子散斑干涉条纹处理偏微分方程方法的回顾与展望,激光与光电子学进展,2010,47(021201):1~12
[3] A.E. Ennos, Visual observation of surface vibration model pattern,Nature, 1969, 212:652~660
[4]方强,陈家碧,全息散斑计量学,北京:科学出版社,1995, 51~150
[5] A. Makovski, Time-lapse interferometry and conturing using television systems, Appl. Opt., 1971, 10(3):2772~2727
[6] S. Nakadate, T. Yatagai, H. Saito,Electronic speckle pattern interferometry using digital image Processing technique,Appl.Opt., 1980, 19(11):1879~1883
[7] X.L. Gong, S. Toyooka, Investigation on mechanism of plastic deformation by digital speckle pattern interferometry, Experimental Mechanics, 1999, 39:25~29
[8] C. Quan, C.J. Tay, F. Yang et al., Phase extraction from a single fringe pattern based on guidance of an extreme map, Appl. Opt., 2005, 44(23):4814~4821
[9]秦玉文,戴嘉彬,陈金龙,电子散斑方法的进展,力学,1996,11(4):410~416
[10] F.P. Chiang, D. Li, W. Radom, Speckle Patterns for displacement and Strain measurement : Some recent advances, Opt. Eng., 1985, 24:936~943
[11]张芳,电子散斑干涉条纹图的偏微分方程处理方法及相位提取,硕士学位论文,天津大学,2006
[12] C.J. Tay, C. Quan, L. Chen et al., Phase extraction from electronic speckle patterns by statistical analysis, Opt. Commun., 2004, 236:259~269
[13]罗志勇,陈朝晖,顾英姿等,基于数值模拟的高准确度五步相移算法研究,光学学报,2006,26(11):1687~1690
[14]王巍巍,散斑干涉技术实验研究及无损检测方面的应用,硕士学位论文,哈尔滨工程大学,2008
[15]杨国标,章彰,电子散斑干涉法在铝合金材料结构内部柱状缺陷检测中的应用研究,计量学报,2008,29(4A):191~194
[16]周文静,彭娇,于瀛洁,基于数字全息技术的变形测量,光学精密工程,2005,13: 46~51
[17] P.S. Huang, Q.J.Hu, F.Chiang, Double three-step shifting algorithm, Appl. Opt., 2002,41(22):4503~4509
[18] P.S.Huang, S. Zhang, Fast three-step phase-shifting algorithm, Appl. Opt., 2006, 45(21):5086~5091
[19] Y. Awatsuji, A. Fujii, T. Kubota et al., Parallel three-step phase-shifting digital holography, Appl. Opt., 2006, 45(13):2995~3002
[20] F. Yang, X. He, Two-step phase-shifting fringe projection profilometry: intensity derivative approach, Appl. Opt., 2007,46(29):7172~7178
[21] T. Aoki, T. Sotomaru, Two-dimension phase unwrapping by direct elimination of rotational vector fields from phase gradient, obtained by heterodyne techniques, Pro. SPIE, 1998, 3(478): 162~169
[22] J. J. Hunthey, H. Satdner, Temporal phase-unwrapping algorithm for automated interferogram analysis, Appl. Opt., 1993, 32(17):3047~3052
[23]惠梅,邓年茂,王东生等,基于跳变线估测的相位包裹去除法,光电子·激光, 2003, 14(7):745~748
[24] Q. Yu, X. Sun, X. Liu et al., Spin filtering with curve windows for interferometric fringe patterns, Appl. Opt., 2002,41: 2650~2654
[25] J. Villa, J. A. Quiroga, I. de la Rosa, Regularized quadratic cost function for oriented fringe-pattern filtering, Opt.Lett., 2009,34: 1741~1743
[26] C. Tang, W. Wang, H. Yan et al., Tangent least-squares fitting filtering method for electrical speckle pattern interferometry phase fringe patterns, Appl. Opt., 2007, 46(15):2907~2913
[27] C.Tang, L.Han, H.Ren et al., The oriented-cuple partial differential equations for filtering in wrapped phase patterns, Opt. Express, 2009,17:5606~5617
[28] C. Tang, H. Ren, L. Wang et al., Oriented couple gradient vector fields for skeletonization of gray-scale optical fringe patterns with high density, Appl. Opt.,2010,49(16): 2979~2984
[29] X. Zhou, J. P. Baird, J. F. Arnold, Fringe-orientation estimation by use of a Gaussian gradient filter and neighboring-direction averaging, Appl. Opt., 1999,38: 795-804
[30] Q. F. Yu, X. Y. Sun, Removing speckle noise and extracting the skeletons from a single speckle fringe pattern by spin filtering with curved-surface window, Opt. Eng., 2003,42(1):68~74
[31] L. Hong, Y. Wan, A. Jain, Fingerprint image enhancement: algorithm and performance evaluation, IEEE Trans. Pattern Anal. Mach. Intell., 1998,20(8), 777~789
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