Feature adaptive sampling for scanning electron microscopy
- A new method for the image acquisition in scanning electron microscopy (SEM) was introduced. The method used adaptively increased pixel-dwell times to improve the signal-to-noise ratio (SNR) in areas of high detail. In areas of low detail, the electron dose was reduced on a per pixel basis, and a-posteriori image processing techniques were applied to remove the resulting noise. The technique was realized by scanning the sample twice. The first, quick scan used small pixel-dwell times to generate a first, noisy image using a low electron dose. This image was analyzed automatically, and a software algorithm generated a sparse pattern of regions of the image that require additional sampling. A second scan generated a sparse image of only these regions, but using a highly increased electron dose. By applying a selective low-pass filter and combining both datasets, a single image was generated. The resulting image exhibited a factor of ~ ‰3 better SNR than an image acquired with uniform sampling on a Cartesian grid and the same total acquisition time. This result implies that the required electron dose (or acquisition time) for the adaptive scanning method is a factor of ten lower than for uniform scanning.
Document Type: | Article |
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Author: | Tim DahmenORCiD, Michael Engstler, Christoph PaulyORCiD, Patrick TrampertORCiD, Niels de JongeORCiD, Frank MücklichORCiD, Philipp SlusallekORCiD |
URN: | urn:nbn:de:bsz:291:415-3120 |
DOI: | https://doi.org/10.1038/srep25350 |
ISSN: | 2045-2322 |
Parent Title (English): | Scientific Reports |
Volume: | 6 |
Pagenumber: | 25350 |
Language: | English |
Year of first Publication: | 2016 |
Release Date: | 2022/11/18 |
Impact: | 04.259 (2016) |
Funding Information: | European Research Project NOTOX (FP7-267038), the DFG grant IMCL (AOBJ: 600875) and the “Landesforschungsförderungsprogramm des Saarlandes” (WT/2-LFFP 15/09). The authors thank the DFKI GmbH and Saarland University for additional funding and for providing the necessary infrastructure and E. Arzt for his support through INM. |
Scientific Units: | Innovative Electron Microscopy |
Open Access: | Open Access |
Signature: | INM 2016/43 |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |