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Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images.

ABSTRACT: Super-resolution techniques like PALM and STORM require accurate localization of single fluorophores detected using a CCD. Popular localization algorithms inefficiently assume each photon registered by a pixel can only come from an area in the specimen corresponding to that pixel (not from neighboring areas), before iteratively (slowly) fitting a Gaussian to pixel intensity; they fail with noisy images. We present an alternative; a probability distribution extending over many pixels is assigned to each photon, and independent distributions are joined to describe emitter location. We compare algorithms, and recommend which serves best under different conditions. At low signal-to-noise ratios, ours is 2-fold more precise than others, and 2 orders of magnitude faster; at high ratios, it closely approximates the maximum likelihood estimate.

SUBMITTER: Larkin JD

PROVIDER: S-EPMC3503144 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images.

Larkin Joshua D JD Cook Peter R PR

Optics express 20120701 16

Super-resolution techniques like PALM and STORM require accurate localization of single fluorophores detected using a CCD. Popular localization algorithms inefficiently assume each photon registered by a pixel can only come from an area in the specimen corresponding to that pixel (not from neighboring areas), before iteratively (slowly) fitting a Gaussian to pixel intensity; they fail with noisy images. We present an alternative; a probability distribution extending over many pixels is assigned ...[more]

PMID: 23038398

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