Poisson noise removal from high-resolution STEM images based on periodic block matching

Scanning transmission electron microscopy (STEM) provides sub-ångstrom, atomic resolution images of crystalline structures. However, in many applications, the ability to extract information such as atom positions, from such electron micrographs, is severely obstructed by low signal-to-noise ratios o...

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Veröffentlicht in:Advanced structural and chemical imaging Jg. 1; H. 1; S. 1 - 19
Hauptverfasser: Mevenkamp, Niklas, Binev, Peter, Dahmen, Wolfgang, Voyles, Paul M, Yankovich, Andrew B, Berkels, Benjamin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 25.03.2015
Springer Nature B.V
Schlagworte:
Atomic structure
Biological Microscopy
Characterization and Evaluation of Materials
Chemistry and Materials Science
Computer simulation
Electron micrographs
Electrons
Filtration
Image acquisition
Image resolution
Image transmission
Imaging and Modeling in Electron Microscopy - Recent Advances
Inorganic materials
Matching
Materials Science
Noise
Noise levels
Noise reduction
Periodic structures
Scanning transmission electron microscopy
Spectroscopy/Spectrometry
Periodic search
Precision
Non-local means
3D transform shrinkage
Poisson noise
Image denoising
Block matching
STEM
ISSN:2198-0926, 2198-0926
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Scanning transmission electron microscopy (STEM) provides sub-ångstrom, atomic resolution images of crystalline structures. However, in many applications, the ability to extract information such as atom positions, from such electron micrographs, is severely obstructed by low signal-to-noise ratios of the acquired images resulting from necessary limitations to the electron dose. We present a denoising strategy tailored to the special features of atomic-resolution electron micrographs of crystals limited by Poisson noise based on the block-matching and 3D-filtering (BM3D) algorithm by Dabov et al. We also present an economized block-matching strategy that exploits the periodic structure of the observed crystals. On simulated single-shot STEM images of inorganic materials, with incident electron doses below 4 C/cm 2 , our new method achieves precisions of 7 to 15 pm and an increase in peak signal-to-noise ratio (PSNR) of 15 to 20 dB compared to noisy images and 2 to 4 dB compared to images denoised with the original BM3D.
Bibliographie:ObjectType-Article-1
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ISSN:2198-0926
2198-0926
DOI:10.1186/s40679-015-0004-8