Systematic errors due to polynomial interpolation in Digital Image Correlation. Analysis of some interpolating kernels and experimental validation

The accuracy of image correlation algorithms is severely affected by errors introduced by the interpolation step. This article surveys some of the most common interpolating and approximating kernels, focusing on the various sources of error—signal attenuation, phase errors and frequency spectrum—to identify the best performing algorithms. The results of the analysis are experimentally validated by comparing the Digital Image Correlation estimated displacements with the interferometric estimated values