Iteratively Weighted Phase Motion Estimation Method Based on Log‐Gabor Wavelets for Structural Displacement Measurement

Phase‐based motion estimation (PME) provides a noncontact approach to structural displacement measurement, but its local phase estimation is easily affected by the average intensity of the illumination, and there is a phase wrapping phenomenon under large‐amplitude vibrations or high‐frequency noise disturbances. To overcome these limitations, a novel weighted log‐Gabor motion estimation (WLGME) method is proposed in this work to estimate structural motion by combining the prescribed multiscale log‐Gabor bank with two‐frame amplitude confidence and Huber residual weights through an iteratively reweighted least‐squares (IRLS) algorithm. A solution framework for time‐varying parameter updating and displacement accumulation is constructed, and two cantilever experiments are carried out to evaluate the robustness and measurement accuracy of different algorithms. The results showed that the WLGME method reduces the mean absolute error (MAE) and root mean square error (RMSE) by over 50% compared with the conventional PME method. The controlled numerical experiment further indicated that the weighting components have condition‐dependent effects. The motion‐factor sweep and closed‐cycle diagnostic results demonstrated that the multiplicative fusion has a conditional advantage at larger interframe motion, and the residual‐only weighting has a lower drift of underamplitude‐independent outliers.