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Proceedings Paper

Poisson shot noise parameter estimation from a single scanning electron microscopy image
Author(s): Stephen Kockentiedt; Klaus Tönnies; Erhardt Gierke; Nico Dziurowitz; Carmen Thim; Sabine Plitzko
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Paper Abstract

Scanning electron microscopy (SEM) has an extremely low signal-to-noise ratio leading to a high level of shot noise which makes further processing difficult. Unlike often assumed, the noise stems from a Poisson process and is not Gaussian but depends on the signal level. A method to estimate the noise parameters of individual images should be found. Using statistical modeling of SEM noise, a robust optimal noise estimation algorithm is derived. A non-local means noise reduction filter tuned with the estimated noise parameters on average achieves an 18% lower root-mean-square error than the untuned filter on simulated images. The algorithm is stable and can adapt to varying noise levels.

Paper Details

Date Published: 19 February 2013
PDF: 13 pages
Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 86550N (19 February 2013); doi: 10.1117/12.2008374
Show Author Affiliations
Stephen Kockentiedt, Otto-von-Guericke-Univ. Magdeburg (Germany)
Federal Institute for Occupational Safety and Health (Germany)
Klaus Tönnies, Otto-von-Guericke-Univ. Magdeburg (Germany)
Erhardt Gierke, Federal Institute for Occupational Safety and Health (Germany)
Nico Dziurowitz, Federal Institute for Occupational Safety and Health (Germany)
Carmen Thim, Federal Institute for Occupational Safety and Health (Germany)
Sabine Plitzko, Federal Institute for Occupational Safety and Health (Germany)


Published in SPIE Proceedings Vol. 8655:
Image Processing: Algorithms and Systems XI
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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