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Signal‐to‐noise ratio estimation on SEM images using cubic spline interpolation with Savitzky–Golay smoothing
Author(s) -
SIM K.S.,
KIANI M.A.,
NIA M.E.,
TSO C.P.
Publication year - 2014
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12089
Subject(s) - spline interpolation , interpolation (computer graphics) , bicubic interpolation , smoothing , smoothing spline , noise (video) , scanning electron microscope , mathematics , algorithm , computer science , artificial intelligence , optics , statistics , physics , bilinear interpolation , image (mathematics)
Summary A new technique based on cubic spline interpolation with Savitzky–Golay noise reduction filtering is designed to estimate signal‐to‐noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first‐order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real‐time SEM images, without generating corruption or increasing scanning time.