Unbiased roughness measurements from low signal-to-noise ratio scanning electron microscope images

Abstract

Background: Measuring and subtracting scanning electron microscope (SEM) noise from a biased measurement of roughness leads to an unbiased roughness measurement. This unbiasing procedure becomes harder as the noise in the image increases. For low image signal-to-noise ratio (SNR) (below about 2), unbiased roughness measurement becomes less reliable.Aim: It is important to understand the mechanism for the sensitivity of unbiased roughness accuracy to linescan SNR to look for ways to improve unbiased roughness measurement for very noisy images.Approach: Using a combination of mathematical analysis, simulations, and experimental data, the role of pixel size and pitch in the SNR sensitivity are explored.Results: All evidence points to the correlation of edge detection noise to true edge position as the cause of the errors in unbiased roughness measurement for very noisy images. For small pitch patterns, changes in feature edge position caused by feature roughness will cause changes to the linescan slope, which in turn changes the sensitivity of edge detection to SEM image noise.Conclusions: Smaller pixel sizes and larger feature sizes are less sensitive to the SNR effects described here. For any algorithm used to measure unbiased roughness, the impact of linescan SNR must be carefully assessed.