title: Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing.
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.
authors.affiliation: Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia.
authors.forename: K S
authors.initials: KS
authors.lastname: Sim
authors.forename: M A
authors.initials: MA
authors.lastname: Kiani
authors.forename: M E
authors.initials: ME
authors.lastname: Nia
authors.forename: C P
authors.initials: CP
authors.lastname: Tso
mesh_terms: D000818:Animals; D009033:Culicidae / Q000648:ultrastructure; D005121:Extremities / Q000033:anatomy & histology; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008855:Microscopy, Electron, Scanning / Q000379:methods*; D059629:Signal-To-Noise Ratio
keywords: Additive white Gaussian noise; electron microscope; signal-to-noise ratio