Analytical methods for superresolution dislocation identification in dark-field X-ray microscopy
Abstract We develop several inference methods to estimate the position of dislocations from images generated using dark-field X-ray microscopy (DFXM)—achieving superresolution accuracy and principled uncertainty quantification. Using the framework of Bayesian inference, we incorporate...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer US
2022
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| Online Access: | https://hdl.handle.net/1721.1/144366 |