Performance of a gradient‐based shift estimator in a spatially sparse data environment: tracking the sub‐pixel motion of fluorescent particles

Through a series of numerical simulations, we investigate the suitability of a relatively new gradient‐based particle‐tracking algorithm for efficiently quantifying sub‐pixel shifts of fluorescently labelled cells or particles from a sequence of video microscopy images. The algorithm excels at estimating sub‐0.5 pixel per frame shifts in both data‐dense (e.g. laser speckle imaging) and data‐sparse (e.g. fluorescence imaging) applications. No upsampling (i.e. interpolation) is required to achieve the sub‐pixel shift resolution, and thus the approach avoids the complexity and potential errors associated with the interpolation process. An efficient matlab sub‐routine is provided for implementing the algorithm.