Background

High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images.

Objective

This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements.

Methods

First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared.

Results

SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation.

Conclusions

Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.

中文翻译：

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超分辨率数字图像相关（SR-DIC）：高倍率图像拼接的替代选择

背景

高分辨率数字图像相关性（DIC）测量是以前通过拼接相邻图像而产生的，通常需要很短的工作距离。另外，图像处理社区已经开发了超分辨率（SR）成像技术，该技术通过组合多个重叠图像来提高分辨率。

客观的

这项工作研究了超高分辨率与数字图像相关性的新颖配对，作为产生高分辨率全场应变测量的替代方法。

方法

首先，执行图像重建测试，比较三种先前发布的SR算法复制高分辨率图像的能力。其次，使用低分辨率和超分辨率图像将应用的翻译与DIC测量进行比较。第三，将环形样品机械变形，并比较低分辨率和超分辨率图像的DIC应变测量结果。

结果

SR测量显示出与低分辨率图像相比有所改善，尽管它们不能完美地复制高分辨率图像。与低分辨率替代品相比，SR-DIC展示出减少的误差并提高了测量刚体平移的信心，并且还显示出了用于环变形应变测量的空间分辨率的提高。

结论

超分辨率成像可以与数字图像相关性有效地配对，从而提供改进的空间分辨率，减少的误差和更高的测量置信度。