Multivariate analysis of hyperspectral hard X‐ray images. (12th February 2013)

• Record Type: Journal Article
• Authors: Egan, Christopher K.; Jacques, Simon D. M.; Cernik, Robert J.
• Is Part Of: X-ray spectrometry. Volume 42:Number 3(2013:May/Jun.)
• Page Start: 151
• Page End: 157
• Publication Date: 2013-02-12
• Subjects: X-ray spectroscopy -- Periodicals; 543.62
• DOI: 10.1002/xrs.2448
• Languages: English
• ISSNs: 0049-8246

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>This article describes methods to analyse and process hyperspectral hard X‐ray imaging data. We focus on the use of multivariate techniques that exploit the spectral information to make informed decisions on the material content within each pixel of an X‐ray image. These analysis methods have the ability to auto‐segment data without prior knowledge of the sample composition or structure, and are particularly useful for studying completely unknown, diluted or complex specimens. We demonstrate the methods on a variety of hard X‐ray images including X‐ray fluorescence and absorption data recorded using a hard X‐ray imaging spectrometer. The multivariate methods described are very powerful with the ability to segment, distinguish and, in some cases, identify different materials within a single X‐ray image. Potential uses of hyperspectral X‐ray imaging are discussed varying from materials science to industrial or security applications. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>