title: A nonlinear filtering algorithm for denoising HR(S)TEM micrographs.
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.
authors.affiliation: Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Jülich Research Centre, Jülich, 52425, Germany; Central Facility for Electron Microscopy (GFE), RWTH Aachen University, Aachen 52074, Germany; Peter Grünberg Institute, Jülich Research Centre, Jülich 52425, Germany. Electronic address: h.du@fz-juelich.de.
authors.forename: Hongchu
authors.initials: H
authors.lastname: Du
keywords: Denoising; Filtering; HR(S)TEM; Image processing; Noise reduction; Nonlinear filter