Experimental assessment of noise robustness of the forward-additive, symmetric-additive and the inverse-compositional Gauss-Newton algorithm in digital image correlation

•Fully experimental assessment of noise-induced bias for Forward-Additive, Symmetric-Additive, and Inverse-Compositional formulation.•The influence of spatial intensity gradients is experimentally tested.•The effect of image noise on noise-induced bias is experimentally investigated.•The Inverse-Compositional formulation is confirmed to be not affected by noise-induced-bias.•Whatever the formulation, if the contrast is above 20%, the noise-induced bias appears to be a tiny fraction of the total error.