Adaptive undermatched systematic error mitigation algorithm considering spatial continuity in digital image correlation

Abstract In the measurement of inhomogeneous complex deformations using the digital image correlation (DIC) method, systematic errors arising from undermatched shape functions are a significant source of inaccuracy, often surpassing the effects of other errors like random noise and grey-level interpolation errors. This study focuses primarily on mitigating these undermatched systematic errors. In this work, the traditional model corresponding to such errors is extended to analyse the entire subset region comprehensively. Based on this model, a novel mitigation method is proposed, which incorporates spatial continuity considerations. By averaging the recalculated displacement results for each pixel, this approach significantly minimizes potential errors introduced during calculation and achieves more accurate estimations of actual displacements when dealing with complex deformation characterization.