Minimizing the total strain error in point-wise least squares using rotated gaussian weight strain filter (RGW-SF) in digital image correlation

•A rotated Gaussian weight strain filter (RGW-SF) based on the point-wise least squares (PLS) is proposed to tackle the selection of the proper smooth window size for complex strain field measurement.•The systematic and random strain errors of the RGW-SF method are derived.•three weight parameters (i.e., σx,σy, and θ) in the RGW function cooperate to select an optimum smooth window by minimizing the derived total strain error of RGW-SF, which is composed of the systematic and random strain errors.•The RGW-SF method produces more accurate strain fields than PLS method and the other method using changeable smooth window size. and it needs no additional effort to tune the smooth window size as required in PLS.