Journal Article

FZJ-2018-05458

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png A nonlinear filtering algorithm for denoising HR(S)TEM micrographs

Du, H. (Corresponding author)FZJ*

2015
Elsevier Science Amsterdam

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Please use a persistent id in citations: doi:10.1016/j.ultramic.2014.11.012

Abstract: Noise reduction of micrographs is often an essential task in high resolution (scanning) transmission electron microscopy (HR(S)TEM) either for a higher visual quality or for a more accurate quantification. Since HR(S)TEM studies are often aimed at resolving periodic atomistic columns and their non-periodic deviation at defects, it is important to develop a noise reduction algorithm that can simultaneously handle both periodic and non-periodic features properly. In this work, a nonlinear filtering algorithm is developed based on widely used techniques of low-pass filter and Wiener filter, which can efficiently reduce noise without noticeable artifacts even in HR(S)TEM micrographs with contrast of variation of background and defects. The developed nonlinear filtering algorithm is particularly suitable for quantitative electron microscopy, and is also of great interest for beam sensitive samples, in situ analyses, and atomic resolution EFTEM.

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Contributing Institute(s):

1. Mikrostrukturforschung (PGI-5)

Research Program(s):

1. 143 - Controlling Configuration-Based Phenomena (POF3-143) (POF3-143)

Appears in the scientific report 2018

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Database coverage:
; BIOSIS Previews ; Current Contents - Life Sciences ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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