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Gaussian‐Taylor signal‐to‐noise ratio estimation for scanning electron microscope images
Author(s) -
SIM K.S.,
LEE J.K.,
LAI M.A.,
TSO C.P.
Publication year - 2009
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/j.1365-2818.2009.03194.x
Subject(s) - interpolation (computer graphics) , gaussian noise , mathematics , spline interpolation , noise (video) , gaussian , piecewise , autoregressive model , quadratic equation , signal to noise ratio (imaging) , algorithm , statistics , physics , artificial intelligence , computer science , mathematical analysis , bilinear interpolation , geometry , quantum mechanics , image (mathematics) , motion (physics)
Summary A new and robust parameter estimation technique, named Gaussian‐Taylor interpolation, is proposed to predict the signal‐to‐noise ratio (SNR) of scanning electron microscope images. The results of SNR and variance estimation values are tested and compared with piecewise cubic Hermite interpolation, quadratic spline interpolation, autoregressive moving average and moving average. Overall, the proposed estimations for noise‐free peak and SNR are most consistent and accurate to within a certain acceptable degree compared with the others.