Effects of compressed speckle image on digital image correlation for vibration measurement

Digital image correlation (DIC) can accurately measure subpixel displacement field based on speckle images. However, in vibration measurement, the extensive high-resolution images captured by DIC systems impose significant data transmission and storage requirements on hardware. A framework combining image compression techniques with DIC methods is proposed. The framework effectively reduces the memory footprint of images while preserving the primary speckle features with subpixel errors. The DIC Challenge 2.0 image sets are employed in simulation to study the effects of compressing images on data storage and 2D DIC measurements, and the effectiveness are compared between JPEG and JPEG 2000 image compression techniques. A cantileverbeam is adopted to experimentally investigate the impacts of the compressed image sets on 3D surface deformation and vibration response measurement. The proposed framework is a valuable option for DIC vibration measurement with high efficiency, the JPEG lossy compression and JPEG 2000 lossless compression each has its own characteristics in performance of DIC based vibration measurement.

Automated summary

Digital image correlation (DIC) accurately measures subpixel displacement field based on speckle images. To address the high data transmission and storage requirements caused by extensive high-resolution images, a framework combining image compression techniques with DIC methods is proposed. The framework reduces the memory footprint of images while preserving the primary speckle features with subpixel errors.