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An improvement to the existing technique of quantifying signal‐to‐noise ratio (SNR) of scanning electron microscope (SEM) images using piecewise cubic Hermite interpolation (PCHIP) technique is proposed. The new technique uses an adaptive tuning onto the PCHIP, and is thus named as ATPCHIP. To test its accuracy, 70 images are corrupted with noise and their autocorrelation functions are then plotted...
A new signal-to-noise ratio (SNR) estimation technique is proposed for the scanning electron microscope image. Based on only a single image, an estimation technique named B-spline is proposed. Three existing techniques are applied to compare with the performance of the proposed method in terms of the zero-offset point, SNR and percentage error. They are the nearest neighborhood, first order interpolation,...
This paper proposes a new signal-to-noise ratio (SNR) estimation technique on scanning electron microscope (SEM) image, using linear regression. The method is based on the single image approach. Four good quality images are used to compare the proposed method and the existing methods: nearest neighborhood, first order interpolation and piecewise cubic Hermite interpolation. The results are compared...
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