The error of digital image correlation (DIC) displacement field measurement is always conflicted with the iteration times of algorithm. To reduce the calculation error, the number of iterations has to be increased, which will result in a heavy computing burden. However, the error of the non-iteration method is usually high. To solve the problem, a BP neural network-based error compensation method is proposed. The non-iteration optical flow algorithm is selected as analytical example and its error is also analyzed. The displacement measurement of a simulated speckle image and its error are used as training data. The displacement measurement result is compensated by the predicted value. The compensation experiment is carried out and it shows that the error after compensation drops by 50% and the histogram of the error is also reduced.