A Spatial Resolution-Based Evaluation Method for Subpixel Registration Algorithms

Digital image correlation (DIC) technology is widely employed in speckle-based measurement techniques, including X-ray speckle tracking. By enhancing DIC’s measurement capability to the subpixel scale through subpixel registration technology, the accuracy of such tracking methods is significantly improved. Consequently, selecting an appropriate subpixel registration algorithm becomes crucial for advancing the precision of both DIC and its application in tracking methods. Nevertheless, current evaluation approaches for these algorithms overlook spatial resolution—an essential metric not only for X-ray speckle tracking but also for other comparable methodologies. Inspired by the modulation transfer function, this study proposes a novel evaluation method that uses the root mean square error of displacement measurement at different spatial frequencies to assess spatial resolution. Two widely used subpixel registration algorithms—the peak-finding algorithm and the iterative spatial domain cross-correlation algorithm—are evaluated and compared. The result strongly contrasts with traditional evaluations based on ideal translational conditions, and underscores the necessity of incorporating spatial resolution and speckle size into algorithm selection criteria for practical applications.