Experimental analysis of the errors due to polynomial interpolation in digital image correlation

Digital image correlation attempts to estimate displacement fields by digitally correlating two images acquired before and after motion. To do so, pixel intensity has to be interpolated at non-integer locations. The ideal interpolator is the sinc, but as it requires infinite support, it is not normally used and is replaced by polynomials. Polynomial interpolation produces visually appealing results but introduces positional errors in the signal, thus causing the digital image correlation algorithms to converge to incorrect results. In this work, an experimental campaign is described, that aims to characterise the errors introduced by interpolation, focusing in particular on the systematic error and the standard deviation of displacements.