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Image noise cross-correlation for signal-to-noise ratio estimation in scanning electron microscope images
1Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia. kssim@mmu.edu.my
Abstract:
A new and robust parameter estimation technique, named image noise cross-correlation, 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 nearest neighborhood and first-order interpolation. Overall, the proposed method is best as its estimations for the noise-free peak and SNR are most consistent and accurate to within a certain acceptable degree, compared with the others.
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