KEYWORDS: Super resolution microscopy, Chemical analysis, Sensors, Image processing software, Molecular assembly, Proteins, Glasses, Interfaces, Biosensors, Molecules, Point spread functions, Signal to noise ratio, Detection and tracking algorithms, Charge-coupled devices, Super resolution, Data modeling, Algorithm development, Computer simulations, Microscopy
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.
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