数字图像相关技术中插值偏差的理论估计

数字图像相关测量的普及提出了建立散斑质量评价体系要求,即发展针对不同的数字散斑图能够评估测量精度的标准方法.其中,数字图像相关计算中插值误差引起亚像素位移系统偏差(插值偏差)的估计是评价散斑质量的重要参数,然而至今插值偏差与散斑图结构及其插值方法之间的深层机制仍然不明,而且缺乏快速有效的手段估计插值偏差的量级.基于傅里叶方法获得了插值偏差的解析表达式.在满足采样定理的情况下,对其简化得到了插值偏差的带限近似形式和正弦近似形式.插值偏差的正弦近似形式解释了插值偏差随亚像素平移呈正弦形式变化的现象.基于插值偏差的正弦近似公式,提出了决定插值算法用于相关匹配优劣的插值偏差核概念,它表征了插值算法对散斑图特定频率的偏差响应,插值偏差是由插值偏差核与图像功率谱乘积的积分决定的.基于理论分析,提出了一种通过散斑频谱和插值偏差核估计插值偏差的简便有效算法,较之于传统的散斑图平移方法有明显的速度优势.分析了模板大小对估计精度的影响,并通过模拟进行了验证.解释了插值偏差产生的深层机理,解决了长久以来插值偏差难以快速估计的问题.不仅可以用于插值偏差估计,也可以用于插值算法优化,滤波模板选取等问题.对建立散斑质量评价体系,从而制作方便用户的水转印标准散斑也有推动作用.      

关于数字图像相关中曲面拟合法的几点讨论

曲面拟合法求解亚像素位移是数字图像相关亚像素位移定位中的一种重要方法,它具有抗噪声能力较强、精度高、计算效率高等优点,在实际应用中多被采用.本文就该算法中影响亚像素位移定位精度的各要素进行了详细讨论,并用计算机生成的模拟散斑图和金属试件的刚体平移实验进行了验证,结果表明,整像素搜索时选取不同的计算窗口对计算结果的影响最大,而文中所列的几种相关函数的选取对计算结果的影响则可以忽略.     

数字图像相关方法中匹配及过匹配形函数的误差分析

基于图像子区的数字图像相关方法需采用合适的形函数来近似目标图像子区的真实变形。由于实际测量时目标子区的局部变形往往是未知的,实际采用的不同阶次(零阶、一阶和二阶)的形函数不可避免地产生误匹配(欠匹配和过匹配)问题,从而引入位移测量的系统或随机误差。尽管由欠匹配形函数引起的系统误差已被充分认识,由过匹配形函数引起的位移误差仍缺少理论解释。本文首先推导出采用一阶和二阶形函数的数字图像相关方法的随机误差理论公式,随后采用一系列数值实验验证了理论公式的准确性。结果显示:过匹配形函数不会引入额外的系统误差,但会增加随机误差,且二阶形函数的随机误差是一阶形函数的二倍。考虑到由欠匹配一阶形函数引入的系统误差往往远大于过匹配二阶形函数的随机误差,因此在未能确知变形的情况下,推荐使用二阶形函数。     

数字图像相关方法中散斑图的质量评价研究

在利用数字图像相关方法测量物体表面变形时,被测物体表面必需覆盖有灰度随机分布的散斑场,该散斑场作为试件表面变形信息的载体随试件一起变形。在实际情况下,不同的散斑场会显示出完全不同的灰度分布特征,并对数字图像相关方法的测量结果有着重要影响。因此如何定量评价散斑图的优劣是数字图像相关方法中一个重要的基本问题,也是该方法的使用者非常关心的问题。基于最近数字图像相关方法基本理论研究的进展,本文提出平均灰度梯度这一新参数用于散斑图质量的评价。为证实该参数的有效性,本文对五幅明显不同的散斑图进行了精确平移,并将数字图像相关方法测量的位移与预加的平移量进行比较,分析了位移测量结果的均值误差和标准差。结果显示位移测量结果的均值误差和标准差均与散斑图的平均灰度梯度有关,一个好的散斑图应该具有较大的平均灰度梯度。     

超声散斑数字相关法应用于刚体面内转动测量的研究

在激光数字散斑相关法测量理论的基础上,阐述了超声散斑相关法测量的基本原理,并建立了相应的超声散斑数字相关实验分析系统。在实验分析时,首先应用模拟测量的方法对刚体面内转动对散斑场相关性的影响进行了分析;然后应用实验测量的方法再对此进行了分析;最后对刚体未知面内转角进行了实测。实验结果表明,刚体面内转动可测量的最大转角为9°,当转动角度为10°时,误差大于9%。实验中分别应用了爬山搜索法和相关系数拟合法来分别搜索整像素的位移和亚像素的位移。     

超声散斑数字相关法应用于体面内转动测量的研究

在激光数字散斑相关法测量理论的基础上,阐述了超声散斑相关法测量的基本原理,并建立了相应的超声散斑数字相关实验分析系统。在实验分析时,首先应用模拟测量的方法对刚体面内转动对散斑场相关性的影响进行了分析;然后应用实验测量的方法再对此进行了分析;最后对刚体未知面内转角进行了实测。实验结果表明,刚体面内转动可测量的最大转角为9°,当转动角度为10°时,误差大于9%。实验中分别应用了爬山搜索法和相关系数拟合法来分别搜索整像素的位移和亚像素的位移。     

基于多通道滤波技术的散斑条纹图正则化方法

在光测力学中,条纹图正则化是进一步提取条纹位相信息的重要基础。对于散斑条纹图来说,正则化的过程还需能够有效地抑制散斑噪声。本文提出一种基于多通道滤波技术的散斑条纹图正则化方法。通过使用多个Gabor滤波通道对散斑条纹图进行滤波,并且引入与条纹对比度有关的权重因子把各个滤波通道的滤波结果叠加起来,最终得到滤除了散斑噪声的正则化条纹图。数值模拟和实验结果表明,该方法在将散斑条纹图正则化的同时能够有效地滤除条纹图中的散斑噪声,为进一步提取条纹位相奠定了良好的基础。     

利用数字散斑相关法测定聚酰亚胺/SiO2合成薄膜的力学性能

聚酰亚胺 /SiO2 合成薄膜是一种具有优良力热光电性能的薄膜材料,在MEMS工艺中具有广阔的应用前景,其力学性能测量的研究具有非常重要的意义。本文将数字散斑相关技术和微拉伸试验相结合,对厚度为 37μm的聚酰亚胺(polyimide) /二氧化硅(SiO2 )合成薄膜进行了力学性能测量,获得了比较满意的结果。文章给出了测得的弹性模量和泊松比。为了解决数字散斑相关法不能直接测量较大变形的缺陷,本文提出了多级相关算法,并利用亚像素搜索和双线性插值进行了数据处理。     

一种基于半参数回归的加速度计误差模型辨识方法

为了解决加速度计离心机试验中系统误差和未建模误差对加速度计模型辨识的影响,将统计学中的半参数回归方法引入到加速度计的模型辨识中,建立了加速度计的半参数回归模型,提出了一种基于最小二乘-半参数回归模型(LS-SPRM)的估计方法,该估计方法利用最小二乘法估计加速度计的误差模型系数,利用半参数回归方法估计加速度计测试中的系统误差,并通过检验残差是否为白噪声作为判断是否有系统误差的条件。在半参数模型的估计中,采用二阶段估计方法,利用三次样条函数进行非参数部分的估计,并讨论了光滑参数的选取方法。仿真试验结果表明,采用该方法能够较好地补偿由于系统误差和未建模误差带来的影响,使加速度计模型辨识的标准差较普通最小二乘法减小45%左右,估计的残差也减小了近一倍。     

数字图像相关中亚像素位移测量算法的研究

为提高位移测量精度而提出的各种亚像素位移测量算法被认为是数字图像相关方法 中的关键技术之一,详细了解已有各算法的性能无疑具有实际意义. 总结文献中3种 最常用的亚像素位移测量算法,首先用无噪声的计算机仿真散斑图对各算法的性能从计算精 度和计算效率两个方面进行了比较研究,并用实际实验图片对其性能做进一步的研究,结果 显示在图像子区大小相同的情况下,基于空域相关函数迭代的牛顿-拉普森方法计算结果最 为精确、稳定.     

Assessment of Digital Image Correlation Measurement Accuracy in the Ultimate Error Regime: Improved Models of Systematic and Random Errors

The literature contains many studies on assessment of DIC uncertainties, particularly in the ultimate error regime, when the shape function used to describe the material transformation perfectly matches the actual transformation. For pure sub-pixel translations, bias and random errors obtained for experimental or synthetic images show more complex evolution versus the fractional part of displacement than those predicted by the existing theoretical models. Indeed, small deviations arise, mainly around integer values of imposed displacements for noisy images, and they are interpreted as the unrepresentativeness of the underlying hypotheses of the theoretical models. In a first step, differences between imposed and measured displacements are analysed: random error is independent of fractional displacement, and systematic error does not decrease for values close to integer displacements whatever the noise level. Therefore, new prediction models are proposed based on the analysis of identified phenomena from synthetic speckle-pattern 8-bit images. The statistical approach used in this paper generalizes the methods proposed in the literature and mimics the experimental methodology usually used for displacement measurements performed in different subsets in the same image. Two closed-form expressions for the systematic and random errors and a linear interpolation scheme are developed. These models, depending only on image properties and the imposed displacement, are built with a very limited number of parameters. It is then possible to predict the evolution of bias and random errors from one to four images.     

An Error Criterion in Digital Image Correlation for Unknown Deformation Fields and Its Application of Parameters Selection

Digital image correlation (DIC) is a widely used optical metrology for surface deformation measurement. In DIC, the square root of the mean square error (RMS error) and standard deviation error (SD error) are used as quantitative criteria in order to evaluate the accuracy and robustness of a DIC method\algorithm. However, RMS and SD error criteria are computed from prescribed and measured displacements, which indicates that the prescribed displacement fields must be precisely generated. Therefore, it is difficult to quantitatively evaluate the accuracy and robustness of an algorithm\method in practical DIC measurements because imposed displacements are unknown (that’s why DIC measurements are needed). Moreover, the accuracy of DIC measurements highly relies on parameters selection, especially the selections of subset size and shape function. In practice, the subset size and shape function are usually selected according to experience because there are numerous factors (e.g. the quality of speckle image, local displacement field) and uncertainties (e.g. noise level, out-of-plane motion, illumination lighting fluctuation during image capturing) that affect the parameters selection, which makes it difficult to select optimal parameters based on previous works which mainly focused on theoretical deduction in ideal condition. In this paper, an error criterion for evaluating the accuracy of practical DIC measurements with unknown displacements is proposed. Numerical experiments are used to validate the effectiveness and feasibility of the proposed criterion for accuracy evaluation. It is concluded that the square root of the sum of squared forward and backward displacements difference (SFBD) error has a significant positive linear correlation with the widely used SD error in most practical DIC measurements where the mismatch between the frequently-used first- and second-order shape functions and the actual field is usually small. Also, an application of the proposed criterion is presented by real experiments for subset size and shape function selections, which verifies that the proposed error criterion can be effectively used for DIC parameters selection.     

光绘:自由开源的数字散斑图像生成和评价软件

生成数字散斑图像以及对应的变形图像是数字图像相关研究的基础,然而至今仍然缺乏功能齐全、操作简单、界面友好的专业散斑生成和分析软件;研究者需要自行实现相关算法,不仅费时耗力,也增加了出错的可能性.本文发布了一款自由开源的数字散斑图像生成和评价软件:《光绘》.该软件具有散斑图生成、变形图生成、散斑质量评价和散斑图案推荐等功...     

An Improved Error Evaluation in One-Dimensional Deformation Measurements by Linear Digital Image Correlation

Simple analytical error formulas were derived for one-dimensional deformation parameter estimation by an image correlation analysis with linear subpixel interpolation. A two-parameter deformation function was used in the analysis to account for both rigid-body translation and constant displacement gradient in an image subset. Errors in parameter estimation were found to explicitly relate to the image grayscale error consisting of subpixel approximation, image noise (including quantization error), and subset deformation mismatch at each point of the subset. A power-law dependence of the standard deviation of errors in deformation parameter estimation on the subset size was established when random image noise was dominant and it was confirmed by the numerical results of both nonlinear and linear image correlation analyses of synthetic image pairs. The power-law relationship can be used to guide the selection of suitable image quality, subpixel approximation, subset size, and subset deformation function for the desired measurement precision of deformation parameters.     

High-precision sub-pixel interpolation in particle image velocimetry image processing

The task of image interpolation and re-sampling for particle image velocimetry (PIV) is investigated, which is used for window shifting with sub-pixel accuracy and image or window deformation. A new interpolation scheme based on a Gaussian filter is introduced and compared with commonly used and widely accepted interpolation techniques in terms of the achievable root mean square deviation of the displacement estimates.     

Digital speckle correlation for strain measurement by image analysis

This paper is concerned with small strain measurement utilizing the numerical processing of digital images. The proposed method has its theoretical basis in digital signal analysis and, from a methodological point of view, it can be considered as an extension to digital images of the wellknown white light speckle photography technique. That conventional method is based on the analysis of photographic plates that are exposed twice (before and after the specimen deformation) with the image of a random speckle pattern that has been previously printed on the test piece surface. The digital speckle correlation advantages consist of requiring a very simple specimen preparation and, mainly, of allowing the strain field computation just by numerical elaboration of the acquired images. In this paper, the theoretical basis of the technique and some valuable improvements to the known analogous methodologies are presented. Finally, test results for an application of digital speckle correlation are shown and advantages and disadvantages of the technique are elaborated. In addition, further developments in this area are discussed.     

Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant Computations

High-efficiency and high-accuracy deformation analysis using digital image correlation (DIC) has become increasingly important in recent years, considering the ongoing trend of using higher resolution digital cameras and common requirement of processing a large sequence of images recorded in a dynamic testing. In this work, to eliminate the redundant computations involved in conventional DIC method using forward additive matching strategy and classic Newton–Raphson (FA-NR) algorithm without sacrificing its sub-pixel registration accuracy, we proposed an equivalent but more efficient DIC method by combining inverse compositional matching strategy and Gauss-Newton (IC-GN) algorithm for fast, robust and accurate full-field displacement measurement. To this purpose, first, an efficient IC-GN algorithm, without the need of re-evaluating and inverting Hessian matrix in each iteration, is introduced to optimize the robust zero-mean normalized sum of squared difference (ZNSSD) criterion to determine the desired deformation parameters of each interrogated subset. Then, an improved reliability-guided displacement tracking strategy is employed to achieve further speed advantage by automatically providing accurate and complete initial guess of deformation for the IC-GN algorithm implemented on each calculation point. Finally, an easy-to-implement interpolation coefficient look-up table approach is employed to avoid the repeated calculation of bicubic interpolation at sub-pixel locations. With the above improvements, redundant calculations involved in various procedures (i.e. initial guess of deformation, sub-pixel displacement registration and sub-pixel intensity interpolation) of conventional DIC method are entirely eliminated. The registration accuracy and computational efficiency of the proposed DIC method are carefully tested using numerical experiments and real experimental images. Experimental results verify that the proposed DIC method using IC-GN algorithm and the existing DIC method using classic FA-NR algorithm generate similar results, but the former is about three to five times faster. The proposed reliability-guided IC-GN algorithm is expected to be a new standard full-field displacement tracking algorithm in DIC.     

DVC中内部散斑质量评价及计算体素点的优化选择

数字体图像相关方法(digital volume correlation, DVC)是一种可测量物体内部三维全场变形的先进实验力学测试技术, 通过分析由体图像成像设备(如X-ray CT)获取的物体变形前后的三维体图像, DVC可获得物体内部具有亚体素精度的三维变形信息. 在应用DVC测量内部变形时, 被测试样体图像的内部散斑质量对其测量精度有着重要影响. 本文从DVC算法位移测量误差的理论分析和数值模拟实验两方面证实了DVC的位移测量误差与计算子体块的灰度梯度平方和(sum of square subvolume intensity gradient, SSSIG)值呈负相关关系, 即: 计算子体块的SSSIG值越大, 其位移测量精度越高, 因此SSSIG可用于体图像内部散斑质量的定量评价. 尽管直接增加计算子体块尺寸可以增加SSSIG, 但是较大计算子体块内更多的计算点会导致计算量的显著增加. 为此, 本文进一步提出一种计算体素点优化选择方法, 该方法通过将计算子体块中灰度梯度较小的体素点剔除出计算, 以实现在增大计算子体块尺寸的同时不会显著增加计算量. 模拟和真实实验结果显示了该计算体素点优化选择方法的有效性.