| Autor: |
Bertaux N, Allain M, Weizeorick J, Park JS, Kenesei P, Shastri SD, Almer J, Highland MJ, Maddali S, Hruszkewycz SO |
| Jazyk: |
angličtina |
| Zdroj: |
Optics express [Opt Express] 2021 Oct 25; Vol. 29 (22), pp. 35003-35021. |
| DOI: |
10.1364/OE.438945 |
| Abstrakt: |
We have developed and demonstrated an image super-resolution method-XR-UNLOC: X-Ray UNsupervised particle LOCalization-for hard x-rays measured with fast-frame-rate detectors that is an adaptation of the principle of photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), which enabled biological fluorescence imaging at sub-optical-wavelength scales. We demonstrate the approach on experimental coherent Bragg diffraction data measured with 52 keV x-rays from a nanocrystalline sample. From this sample, we resolve the fine fringe detail of a high-energy x-ray Bragg coherent diffraction pattern to an upsampling factor of 16 of the native pixel pitch of 30 μm of a charge-integrating fastCCD detector. This was accomplished by analysis of individual photon locations in a series of "nearly-dark" instances of the diffraction pattern that each contain only a handful of photons. Central to our approach was the adaptation of the UNLOC photon fitting routine for PALM/STORM to the hard x-ray regime to handle much smaller point spread functions, which required a different statistical test for photon detection and for sub-pixel localization. A comparison to a photon-localization strategy used in the x-ray community ("droplet analysis") showed that XR-UNLOC provides significant improvement in super-resolution. We also developed a metric by which to estimate the limit of reliable upsampling with XR-UNLOC under a given set of experimental conditions in terms of the signal-to-noise ratio of a photon detection event and the size of the point spread function for guiding future x-ray experiments in many disciplines where detector pixelation limits must be overcome. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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