1. Non-rigid registration and non-local principle component analysis to improve electron microscopy spectrum images
- Author
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Sarah J. Haigh, Albert K. Oh, Chenyu Zhang, Feridoon Azough, Paul M. Voyles, Rebecca Willett, Thomas J. A. Slater, Andrew B. Yankovich, and Robert Freer
- Subjects
Materials science ,Noise reduction ,Analytical chemistry ,Image registration ,Bioengineering ,02 engineering and technology ,Poisson distribution ,01 natural sciences ,symbols.namesake ,0103 physical sciences ,General Materials Science ,Computer vision ,Electrical and Electronic Engineering ,010302 applied physics ,Pixel ,Noise (signal processing) ,business.industry ,Mechanical Engineering ,General Chemistry ,021001 nanoscience & nanotechnology ,Dark field microscopy ,Dwell time ,Mechanics of Materials ,Computer Science::Computer Vision and Pattern Recognition ,Principal component analysis ,symbols ,Artificial intelligence ,0210 nano-technology ,business - 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.
- Published
- 2016
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