Super-resolution localization microscopy methods rely on accurate and fast localization algorithms. We introduce a simple algorithm for the localization of imaged objects based on the search of the best-correlated center. This approach yields tracking accuracies that are comparable to those of Gaussian fittings in typical low signal-to-noise ratios, but with 6× faster execution. The algorithm can be adapted to localize objects that do not exhibit radial symmetry or have to be localized in higher dimensional spaces.
Siheng He and Henry Hess, "Single molecule localizations by pattern matching," Proc. SPIE 9721, Nanoscale Imaging, Sensing, and Actuation for Biomedical Applications XIII, 97210X (Presented at SPIE BiOS: February 18, 2016; Published: 22 April 2016); https://doi.org/10.1117/12.2213166.
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