Performance of new signal-to-noise ratio estimation for SEM images based on single image noise cross-correlation

Abstract

A new technique for estimation of signal-to-noise ratio in scanning electron microscope images is reported. The method is based on the image noise cross-correlation estimation model recently developed. We derive the basic performance limits on a single image signal-to-noise ratio estimation using the Cramer–Rao inequality. The results are compared with those from existing estimation methods including the nearest neighbourhood (the simple method), the first order linear interpolator, and the autoregressive based estimator. The comparisons were made using several tests involving different images within the performance bounds. From the results obtained, the efficiency and accuracy of image noise cross-correlation estimation technique is considerably better than the other three methods.