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Correction of Scanning Electron Microscope Imaging Artifacts in a Novel Digital Image Correlation Framework

机译:扫描电子显微镜成像伪影在新型数字图像相关框架中的校正

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The combination of digital image correlation (DIC) and scanning electron microscopy (SEM) enables to extract high resolution full field displacement data, based on the high spatial resolution of SEM and the sub-pixel accuracy of DIC. However, SEM images may exhibit a considerable amount of imaging artifacts, which may seriously compromise the accuracy of the displacements and strains measured from these images. The current study proposes a unified general framework to correct for the three dominant types of SEM artifacts, i.e. spatial distortion, drift distortion and scan line shifts. The artifact fields are measured alongside the mechanical deformations to minimize the artifact induced errors in the latter. To this purpose, Integrated DIC (IDIC) is extended with a series of hierarchical mapping functions that describe the interaction of the imaging process with the mechanics. A new IDIC formulation based on these mapping functions is derived and the potential of the framework is tested by a number of virtual experiments. The effect of noise in the images and different regularization options for the artifact fields are studied. The error in the mechanical displacement fields measured for noise levels up to 5% is within the usual DIC accuracy range for all the cases studied, while it is more than 4 pixels if artifacts are ignored. A validation on real SEM images at three different magnifications confirms that all three distortion fields are accurately captured. The results of all virtual and real experiments demonstrate the accuracy of the methodology proposed, as well as its robustness in terms of convergence.
机译:数字图像相关(DIC)和扫描电子显微镜(SEM)的组合能够基于SEM的高空间分辨率和DIC的子像素精度来提取高分辨率的全场位移数据。然而,SEM图像可以表现出相当大量的成像伪影,这可能会严重损害从这些图像测量的位移和菌株的精度。目前的研究提出了统一的一般框架,以纠正三种主导类型的SEM伪像,即空间失真,漂移失真和扫描线偏移。伪像场与机械变形一起测量,以最小化后者的伪像诱导的误差。为此目的,集成DIC(IDIC)与一系列分层映射函数扩展,该映射函数描述了成像过程与机制的相互作用。推导了基于这些映射函数的新IDIC制剂,并且通过许多虚拟实验测试框架的电位。研究了噪声在图像和不同正则化选项中的影响。为噪声水平测量的机械位移场中的误差在为5%的噪声级别内进行的所有案例的常用DIC精度范围内,如果忽略伪像,则大于4个像素。三种不同放大倍数的真实SEM图像的验证确认了所有三个失真字段都被精确捕获。所有虚拟和真实实验的结果展示了所提出的方法的准确性,以及在收敛方面的鲁棒性。

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