光干涉图像的滤波和骨架化算法研究
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摘要
随着激光技术和计算机技术的快速发展,现代光学测量技术已经广泛应用于微位移测量、波面复原及物体表面形貌重构等科研和和工程领域。与传统的光学测量技术相比,现代光学测量技术有很多优点,比如高精度、高灵敏度、数据处理灵活。因此,吸引了大量的实验和理论研究,实验研究主要体现在测试方法多种多样,诸如激光全息干涉法、电子散斑干涉法、云纹干涉法等,虽然各种测量技术的具体方法有所差别,但现代光学测量技术总是通过光干涉图像的形式表征测量场的物理属性,对光干涉图像的数据处理模型和算法理论进行研究是现代光学测量技术中的必备环节。在本论文中,作者主要开展光测条纹的数据处理模型和算法研究,在图像建模的基础上,提出了几种光干涉图像的滤波算法和骨架化算法,并通过对具体干涉图分析说明了算法的性能,主要研究工作概述如下:
提出了基于离散拓扑分析的干涉图滤波算法。作者通过分析基于拓扑梯度滤波模型的原理和特性,发现该模型的滤波算法计算时间长、后续处理复杂。基于此,作者基于拓扑渐进展开理论,将传统拓扑梯度滤波模型中按照像素扰动的思想转换为根据像素边界进行扰动的思想,将拓扑分析滤波的方法应用在干涉图去噪问题上。数值实验和实际干涉图分析表明:该模型和算法可以应用于快速的干涉图像滤波处理和噪声不太大的干涉图滤波处理。
提出了基于贝叶斯估计和复值马尔科夫随机场(Complex-valued Markov Random Field, CMRF)模型的包裹相位图滤波算法。作者通过分析传统的基于贝叶斯估计和CMRF滤波模型的特点,发现其各向同性模型对条纹密集分布的包裹相位图滤波时,在条纹密集分布处会出现模糊的现象。考虑到这一点,作者结合包裹相位图的自身特征,基于贝叶斯估计滤波的原理和修改的CMRF模型,利用干涉数据中处理像素与其邻域像素间的局部交互信息实现包裹相位图的滤波,并通过数值实验和实际干涉图处理结果对算法的性能进行了分析。该算法既可以应用于噪声污染严重和条纹密集分布的包裹相位图滤波处理,也可以应用于条纹稀疏分布的包裹相位图滤波处理。
提出了两种基于灰度图像的干涉图骨架化算法。首先,作者通过研究传统峰值追踪法(Peaking Tracking Method, PTM)的特点,提出了改进的PTM,该算法初衷是以圆形干涉条纹的初始骨架点探测为分析目标,但也可以用于条纹复杂分布的干涉图骨架点探测。其次,提出了基于定位梯度矢量流场(Gradient Vector Flow Fields, GVF)模型的干涉图骨架化算法,干涉条纹的方位角作为了一个有力的援助工具辅助骨架线的探测,实验表明:该模型和算法可以应用于密集条纹分布的干涉图骨架线探测。
研究了骨架化算法在包裹相位图骨架线探测中的应用,并设计和搭建了一套干涉图数据采集装置。作者应用上述两种骨架化算法对采集的干涉图进行了骨架化分析应用,利用具体实验说明了两种干涉图骨架线提取算法的可行性和性能比较,并将定位GVF的骨架化算法与圆拟合方法相结合实现了圆形条纹分布的干涉图的实时跟踪。
During the rapid development of laser technique and computer technique, Modern optical measurement techniques have been becoming widely application on scientific researches and projects, such as Micro-displacement measurement, wavefront retrive and surface tomography reconstruction, etc. Compared with conventional optical measurement techniques, modern optical measurement techniques offer a number of advantages, such as high sensitivity, high precision and convenient data processing. So they have attracted great experiment and theory research, it emerges in experiments that various measurement methods have been produced, such as laser holographic interferometry method, electronic speckle pattern interferometry method and moire interferometry method, etc. Although various details have been used in these measurement methods, it is necessary to research the data processing models and algorithms of optical interferemety image because physical properties of the measurd are charactered by means of optical interferometry fringe patterns in modern optical measurements. This work mainly focuses on the data processing model and algorithm theory research of optical measurement fringe patterns. Based on the image models, the author has presented several filtering algorithms and skeletonization algoritms for the optical fringe patterns, and the performance of algorithms have been explained based on the detailed fringe pattern analysis. Main achievements are summarized as follows.
An interferogram filtering algorithm was presented based on discrete topological analysis. The author found that long computing time and complex post processing techniques were required for the model based on the topological gradient. Based on this, the author presented an improved algorithm in which the topological expansion theory was considered. The author converted the disturbing idea according to the pixel in the traditional topological gradient model to the distrubing idea accoring to the edge of the pixel, and applied it to the interferogram filtering problem. Numerical experiments and real interferogram analysis indicate that the filtering model and algorithm can be used in fast interferogram filtering processing and the interferogram with low noise filtering processing.
An wrapped phase pattern filtering algorithm was presented based on Bayesian evaluation and Complex-valued Markov Random Field (CMRF). The author found that obscure phenomenon was likely to occur for the wrapped phase patterns with dense fringe distribution in traditional isotropic model based on Bayesian evaluation and CMRF. Considering this, the author presented an improved filtering model and algorithm based on Bayesian evaluation and CMRF, in which the denoising image can can be obtained by means of local elicitation information and combined with the characterization of the wrapped phase patterns, and analyzed the performance of the algorithm by numerical experiments and real interferogram processing. The algorithm can be used to the wrapped phase patterns with high noise and dense fringe distribution, as well as applied to the wrapped phase patterns with sparse fringe distribution.
Two skeletonization algrithms of the optical interferogram were presented based on the gray-level data processing technique. Firstly, the author studied the feature of the traditional peaking tracking method (PTM) and proposed an improved PTM based on the goal that detected initial skeleton points of the interferogram with circle fringe distribution, but, it can be used to detect initial skeleton points of the interferogram with complex fringe distribution. Secondly, the author proposed another skeletonization algorithm base on oriented Gradient Vector Flow Fields (GVF), in which the fringe orientation angle can be acted as a powerful aid to perfect the process. Experiments indicate that the algorithm can be used to detect skeletons of the interferogram with dense fringe distribution.
The author studied application of skeletonization algorithms for detecting skeletons of wrapped phase patterns, and an experimental apparatus for data acquisition of interferogram was desighed and established. Above-proposed two skeletonization methods were applied to the real interferogram processing, detailed experiments showed the feasibility and performance comparison of the algorithms, and a real-time tracking method of the interferogram with circle fringe distribution was proposed by combining oriented GVF method and circle fitting method.
提出了基于离散拓扑分析的干涉图滤波算法。作者通过分析基于拓扑梯度滤波模型的原理和特性,发现该模型的滤波算法计算时间长、后续处理复杂。基于此,作者基于拓扑渐进展开理论,将传统拓扑梯度滤波模型中按照像素扰动的思想转换为根据像素边界进行扰动的思想,将拓扑分析滤波的方法应用在干涉图去噪问题上。数值实验和实际干涉图分析表明:该模型和算法可以应用于快速的干涉图像滤波处理和噪声不太大的干涉图滤波处理。
提出了基于贝叶斯估计和复值马尔科夫随机场(Complex-valued Markov Random Field, CMRF)模型的包裹相位图滤波算法。作者通过分析传统的基于贝叶斯估计和CMRF滤波模型的特点,发现其各向同性模型对条纹密集分布的包裹相位图滤波时,在条纹密集分布处会出现模糊的现象。考虑到这一点,作者结合包裹相位图的自身特征,基于贝叶斯估计滤波的原理和修改的CMRF模型,利用干涉数据中处理像素与其邻域像素间的局部交互信息实现包裹相位图的滤波,并通过数值实验和实际干涉图处理结果对算法的性能进行了分析。该算法既可以应用于噪声污染严重和条纹密集分布的包裹相位图滤波处理,也可以应用于条纹稀疏分布的包裹相位图滤波处理。
提出了两种基于灰度图像的干涉图骨架化算法。首先,作者通过研究传统峰值追踪法(Peaking Tracking Method, PTM)的特点,提出了改进的PTM,该算法初衷是以圆形干涉条纹的初始骨架点探测为分析目标,但也可以用于条纹复杂分布的干涉图骨架点探测。其次,提出了基于定位梯度矢量流场(Gradient Vector Flow Fields, GVF)模型的干涉图骨架化算法,干涉条纹的方位角作为了一个有力的援助工具辅助骨架线的探测,实验表明:该模型和算法可以应用于密集条纹分布的干涉图骨架线探测。
研究了骨架化算法在包裹相位图骨架线探测中的应用,并设计和搭建了一套干涉图数据采集装置。作者应用上述两种骨架化算法对采集的干涉图进行了骨架化分析应用,利用具体实验说明了两种干涉图骨架线提取算法的可行性和性能比较,并将定位GVF的骨架化算法与圆拟合方法相结合实现了圆形条纹分布的干涉图的实时跟踪。
During the rapid development of laser technique and computer technique, Modern optical measurement techniques have been becoming widely application on scientific researches and projects, such as Micro-displacement measurement, wavefront retrive and surface tomography reconstruction, etc. Compared with conventional optical measurement techniques, modern optical measurement techniques offer a number of advantages, such as high sensitivity, high precision and convenient data processing. So they have attracted great experiment and theory research, it emerges in experiments that various measurement methods have been produced, such as laser holographic interferometry method, electronic speckle pattern interferometry method and moire interferometry method, etc. Although various details have been used in these measurement methods, it is necessary to research the data processing models and algorithms of optical interferemety image because physical properties of the measurd are charactered by means of optical interferometry fringe patterns in modern optical measurements. This work mainly focuses on the data processing model and algorithm theory research of optical measurement fringe patterns. Based on the image models, the author has presented several filtering algorithms and skeletonization algoritms for the optical fringe patterns, and the performance of algorithms have been explained based on the detailed fringe pattern analysis. Main achievements are summarized as follows.
An interferogram filtering algorithm was presented based on discrete topological analysis. The author found that long computing time and complex post processing techniques were required for the model based on the topological gradient. Based on this, the author presented an improved algorithm in which the topological expansion theory was considered. The author converted the disturbing idea according to the pixel in the traditional topological gradient model to the distrubing idea accoring to the edge of the pixel, and applied it to the interferogram filtering problem. Numerical experiments and real interferogram analysis indicate that the filtering model and algorithm can be used in fast interferogram filtering processing and the interferogram with low noise filtering processing.
An wrapped phase pattern filtering algorithm was presented based on Bayesian evaluation and Complex-valued Markov Random Field (CMRF). The author found that obscure phenomenon was likely to occur for the wrapped phase patterns with dense fringe distribution in traditional isotropic model based on Bayesian evaluation and CMRF. Considering this, the author presented an improved filtering model and algorithm based on Bayesian evaluation and CMRF, in which the denoising image can can be obtained by means of local elicitation information and combined with the characterization of the wrapped phase patterns, and analyzed the performance of the algorithm by numerical experiments and real interferogram processing. The algorithm can be used to the wrapped phase patterns with high noise and dense fringe distribution, as well as applied to the wrapped phase patterns with sparse fringe distribution.
Two skeletonization algrithms of the optical interferogram were presented based on the gray-level data processing technique. Firstly, the author studied the feature of the traditional peaking tracking method (PTM) and proposed an improved PTM based on the goal that detected initial skeleton points of the interferogram with circle fringe distribution, but, it can be used to detect initial skeleton points of the interferogram with complex fringe distribution. Secondly, the author proposed another skeletonization algorithm base on oriented Gradient Vector Flow Fields (GVF), in which the fringe orientation angle can be acted as a powerful aid to perfect the process. Experiments indicate that the algorithm can be used to detect skeletons of the interferogram with dense fringe distribution.
The author studied application of skeletonization algorithms for detecting skeletons of wrapped phase patterns, and an experimental apparatus for data acquisition of interferogram was desighed and established. Above-proposed two skeletonization methods were applied to the real interferogram processing, detailed experiments showed the feasibility and performance comparison of the algorithms, and a real-time tracking method of the interferogram with circle fringe distribution was proposed by combining oriented GVF method and circle fitting method.
引文
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