Resolution enhancement in micro-XRF using image restoration techniques

• Published in: Journal of analytical atomic spectrometry Vol. 37; no. 4; pp. 75 - 758
• Main Authors: Yang, Jie, Zhang, Zhenjie, Cheng, Qiuming
• Format: Journal Article
• Language: English
• Published: London Royal Society of Chemistry 06.04.2022
• Subjects: Algorithms; Error analysis; Image enhancement; Image quality; Image restoration; Knife-edge; Oversampling; Point spread functions; Spatial resolution; Wiener filtering; X ray fluorescence analysis
• ISSN: 0267-9477; 1364-5544
• DOI: 10.1039/d1ja00425e

Micro X-ray fluorescence analysis (micro-XRF) commonly has a lower spatial (lateral) resolution than other elemental mapping techniques like scanning electron microscopy. This disadvantage limits further applications of micro-XRF in microanalysis. In this study, the spatial resolution of micro-XRF was improved by oversampling and image restoration techniques, including both blind and non-blind methods. The point spread function (PSF) for the non-blind method was estimated efficiently by applying both the small point method and the knife-edge method. Three non-blind algorithms-the fast iterative shrinkage-thresholding algorithm, the Wiener filter, and the Richardson-Lucy (RL) method-were tested. The results showed that all these methods could improve the spatial resolution by as much as 26.5%. According to two image quality metrics-the mean squared error and the structural similarity index measure-the results of the RL method were better than those of the others. Compared to the non-blind method, the blind method called "blind deblurring with L0-regularized intensity and gradient prior" only yielded a 12.3% improvement of the resolution, but it obtained a more precise estimation of the size of the PSF. An oversized PSF helps to denoise, but it might reduce the resolution, and vice versa . When the correct PSF was used in the RL method, the improvement of the resolution was as high as 41.6%. A further application on rock samples showed that the technique helped to reduce the resolution variations caused by polychromatic X-rays. This study demonstrated that this technique is promising, but it is still necessary to accumulate more data and design more appropriate algorithms for micro-XRF images. The spatial resolution of micro-XRF can be improved by oversampling and image restoration techniques.