Non-rigid registration and non-local principle component analysis to improve electron microscopy spectrum images

Andrew B. Yankovich, Chenyu Zhang, Albert Oh, Thomas J A Slater, Feridoon Azough, Robert Freer, Sarah J. Haigh, Rebecca Willett, Paul M. Voyles

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Image registration and non-local Poisson principal component analysis (PCA) denoising improve the quality of characteristic x-ray (EDS) spectrum imaging of Ca-stabilized Nd2/3TiO3 acquired at atomic resolution in a scanning transmission electron microscope. Image registration based on the simultaneously acquired high angle annular dark field image significantly outperforms acquisition with a long pixel dwell time or drift correction using a reference image. Non-local Poisson PCA denoising reduces noise more strongly than conventional weighted PCA while preserving atomic structure more faithfully. The reliability of and optimal internal parameters for non-local Poisson PCA denoising of EDS spectrum images is assessed using tests on phantom data.

    Original languageEnglish
    Article number364001
    JournalNanotechnology
    Volume27
    Issue number36
    DOIs
    Publication statusPublished - 1 Aug 2016

    Keywords

    • image denoising
    • multivariate statistical analysis
    • nano characterization
    • spectrum imaging

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