Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing

K S Sim; M A Kiani; M E Nia; C P Tso

doi:10.1111/jmi.12089

Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing

J Microsc. 2014 Jan;253(1):1-11. doi: 10.1111/jmi.12089. Epub 2013 Oct 24.

Authors

K S Sim¹, M A Kiani, M E Nia, C P Tso

Affiliation

¹ Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia.

PMID: 24164248
DOI: 10.1111/jmi.12089

Abstract

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.

Keywords: Additive white Gaussian noise; electron microscope; signal-to-noise ratio.

MeSH terms

Animals
Culicidae / ultrastructure
Extremities / anatomy & histology
Image Processing, Computer-Assisted / methods*
Microscopy, Electron, Scanning / methods*
Signal-To-Noise Ratio*