The contrast-to-noise ratio (CNR) is presented and characterized as a tool for quantitative noise measurement of scanning electron microscope (SEM) images. Analogies as well as differences between the CNR and the widely used signal-to-noise ratio (SNR) are analytically and experimentally investigated. With respect to practical SEM image evaluation using the contrast-to-noise ratio, a standard specimen and an evaluation program are presented.
A statistical model describing signal-noise generation and development along the signal formation process in a standard scanning electron microscope (SEM) using an Everhart-Thornley secondary electron detector is derived. Noise in the detector signal is modeled to originate from a cascade of five signal conversion stages. Based on the derived model, general conclusions are drawn concerning the total signal-to-noise ratio (SNR) at each stage, and the influence of each stage on the total SNR of the detector signal. The model is furthermore applied to a real-world SEM, and verified by experimental data.
A novel dynamic scanning method for noise reduction in scanning electron microscopy and related applications is presented. The scanning method dynamically adjusts the scanning speed of the electron beam depending on the statistical behavior of the detector signal and gives SEM images with uniform and predefined standard deviation, independent of the signal value itself. In the case of partially saturated images, the proposed method decreases image acquisition time without sacrificing image quality. The effectiveness of the proposed method is shown and compared to the conventional scanning method and median filtering using numerical simulations.
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