Image Processing Perspectives of X-Ray Fluorescence Data in Cultural Heritage Sciences
X-ray fluorescence (XRF) analysis of art objects has rapidly gained popularity since the late 2000s due to its increased accessibility to scientists. This introduced an imaging component whereby the XRF image volume provides clues as to which chemical elements are present and where they are located spatially in the object. However, as is the nature of collecting measurements, there are limitations preventing perfect acquisition; e.g, spatial resolution, signal-to-noise ratio, etc. The field of image processing, in part, aims to overcome these limitations. Image processing applications in XRF imaging are only just starting to arise due to the increased interest and availability in XRF analysis. In this article, we aim to reach readers in XRF imaging or image processing in an effort to call for further research in the field. We review the basics of XRF imaging and analysis that is tailored for those unfamiliar with this imaging modality. We then delve into various publications of image processing methods as applied to XRF data. Throughout this article, we examine (and opine on) the XRF field through a lens of the image processing field.
Related Articles
Special Issue on Information Processing in the Arts and Humanities
The papers in this special issue focus on information processing in the arts and humanities. Recent years have witnessed the emergence of various sophisticated information processing tools — including some involving artificial intelligence — that are capable of interrogating increasingly complex datasets in order to tackle challenges arising in a wide range of application domains.
Support for AI Research at the Arts and Humanities Research Council
The Arts and Humanities Research Council (AHRC), part of UK Research and Innovation (UKRI) has supported independent academic research involving information processing tools since its founding in 2005.
Reducing Bias in AI-Based Analysis of Visual Artworks
Empirical research in science and the humanities is vulnerable to bias which, by definition, implies incorrect or misleading findings. Artificial intelligenc...