Issue 5, 2023

Efficient and robust image registration for two-dimensional micro-X-ray fluorescence measurements

Abstract

X-ray fluorescence spectrometry (XRF) is a technique that allows determining non-destructively the composition of elements within a sample. Focussing the excitation X-ray beam to a small spot that is moved in the xy-direction relative to the sample adds lateral information. Such a two-dimensional micro-X-ray fluorescence (2D µ-XRF) spectrometer for desktop use is commercially available providing a resolution down to approximately 10 µm. With a µ-XRF spectrometer, it is inexpensive to take many scans of the same sample. With super-resolution methods, these can potentially be combined into a higher-resolution image. As a prerequisite, the misalignments of multiple scans (shifts and rotation) in the subpixel range have to be detected. We present a method for image registration of multiple images based on expander graphs that provides adjustable tradeoffs between registration quality and running time. We evaluate the algorithms on artificial and real µ-XRF data and we argue that our findings show that subpixel information is present in real µ-XRF data. This is a necessary condition for the applicability of multi-image super-resolution techniques to µ-XRF data in future work.

Graphical abstract: Efficient and robust image registration for two-dimensional micro-X-ray fluorescence measurements

Supplementary files

Article information

Article type
Paper
Submitted
26 okt 2022
Accepted
15 feb 2023
First published
21 feb 2023
This article is Open Access
Creative Commons BY-NC license

J. Anal. At. Spectrom., 2023,38, 1021-1031

Efficient and robust image registration for two-dimensional micro-X-ray fluorescence measurements

F. Bock, A. Gruber, K. Leopold and H. Bruhn, J. Anal. At. Spectrom., 2023, 38, 1021 DOI: 10.1039/D2JA00347C

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