Digital Images Correlation (DIC) measures are widely used in order to calibrate models. It is very common for researchers to use filters on these measurements to improve the measurement resolution (decrease the noise level) before using them with various methodologies. However, the effects of these filters on the tradeoff between spatial resolution and measurement resolution are not fully understood. The objective of the study is to compare seven common denoising/filtering methods for 2D DIC with affine subset shape function, including image filters (Gaussian, Median), frequency filters (Lowpass Butterworth, Holoborodko), local polynomial fitting (Savitzky-Golay filter, cubic splines), and Finite Elements mapping. The proposed methodology to compare the enhancement of these methods is based on the star pattern test cases used in the DIC Challenge 2.0. Hence, this study aims to obtain a general comparison of the filtering methods as opposed to case-dependent approaches. To that end, firstly, the FOLKI-D DIC code is metrologically qualified using the DIC Challenge 2.0 methodology and test cases. Then, the filtering methods are applied to the displacements and strain maps computed with the FOLKI-D code for various DIC subset sizes and filter parameters. It is found that displacement and strain map enhancements vary significantly depending on the filter. Some methods show no improvement (or worsened tradeoff in the strain case), while others achieve similar resolution tradeoffs as DIC codes using quadratic subset shape functions. Finally, it is concluded that the filter choice significantly impacts results, with higher-order lowpass Butterworth, Savitzky-Golay, and Finite Elements mapping methods showing preference over others studied.

数字图像相关（DIC）测量被广泛用于校准模型。研究人员在将这些测量用于各种方法之前，通常会在这些测量中使用滤波器来提高测量分辨率（降低噪声水平）。然而，这些滤波器对空间分辨率和测量分辨率之间的权衡的影响尚不完全清楚。本研究的目的是比较七种常见的具有仿射子集形状函数的 2D DIC 去噪/滤波方法，包括图像滤波器（高斯滤波器、中值滤波器）、频率滤波器（低通巴特沃斯滤波器、Holoborodko 滤波器）、局部多项式拟合（Savitzky-Golay 滤波器、三次样条）和有限元映射。所提出的比较这些方法增强功能的方法基于 DIC 挑战 2.0 中使用的星形模式测试用例。因此，本研究旨在获得过滤方法与案例相关方法的一般比较。为此，首先，FOLKI-D DIC 代码使用 DIC Challenge 2.0 方法和测试用例进行计量合格。然后，将滤波方法应用于使用 FOLKI-D 代码针对各种 DIC 子集大小和滤波器参数计算的位移和应变图。研究发现，位移和应变图的增强效果根据滤波器的不同而有很大差异。一些方法没有表现出任何改进（或应变情况下的权衡恶化），而其他方法则实现了与使用二次子集形状函数的 DIC 代码类似的分辨率权衡。最后得出的结论是，滤波器的选择对结果有显着影响，高阶低通巴特沃斯、Savitzky-Golay 和有限元映射方法显示出优于其他研究的方法。