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dc.contributor.authorÅnes, Håkon Wiik
dc.contributor.authorHjelen, Jarle
dc.contributor.authorSørensen, Bjørn Eske
dc.contributor.authorVan Helvoort, Antonius
dc.contributor.authorMarthinsen, Knut
dc.description.abstractA new method to increase the signal-to-noise ratio S/N of electron backscatter patterns (EBSPs) based upon principal component analysis (PCA) is presented. The PCA denoising method is applied to ten scans of EBSPs from the same region of interest of a recrystallised nickel sample acquired with a decreasing S/N, achieved by reducing the exposure time while increasing the camera gain accordingly. That PCA denoising increases S/N in EBSPs is demonstrated by comparing indexing success rates after both Hough and dictionary indexing (HI and DI) of the Ni patterns having undergone one of four processing routes: i) standard static and dynamic background corrections (standard corrections), ii) standard corrections and pattern averaging with the four closest neighbours, iii) standard corrections and PCA denoising, and iv) standard corrections and pattern averaging followed by PCA denoising. Both pattern averaging and PCA denoising increases the indexing success rates for both indexing approaches for the studied Ni scans, with the former processing route providing the better success rates. The best success rates are obtained after pattern averaging followed by PCA denoising. The potential of PCA denoising to reveal additional pattern details compared to standard corrections and pattern averaging is demonstrated in a pattern from an orthoclase (KAlSi3O8) grain in a geological sample. Software code, and the Ni data sets, are released alongside this article as part of KikuchiPy, an open-source software package dedicated to processing and analysis of EBSPs.en_US
dc.publisherIOP Publishingen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleProcessing and indexing of electron backscatter patterns using open-source softwareen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalIOP Conference Series: Materials Science and Engineeringen_US
dc.description.localcodeContent from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.en_US

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal