A robust focusing and astigmatism correction method for the scanning electron microscope

Abstract

Summary: This paper discusses a new approach to focusing and astigmatism correction based on the fast fourier transforms (FFTs) of scanning electron microscopy (SEM) images. From the FFTs, it is possible to obtain information on the severity of the defocus and astigmatism. This information is then processed by an algorithm to perform real-time focusing and astigmatism correction on the SEM. The algorithm has been tested on defocused and astigmatic images of different samples, including those with highly directional features. Experiments show that the images obtained after running the algorithm can be as good as those that an experienced SEM operator can achieve.

Optomechatronic System For Automated Intra Cytoplasmic Sperm Injection

“…Most focusing algorithms measure the sharpness relying on gradients [8], spectrum analysis [9], image correlation [10], and image variance [11]. We use the image variance method, since its computational efficiency and robustness against noise has been previously noted [12].…”

Visual servoing-based approach for efficient autofocusing in scanning electron microscope

“…Instead of minimizing the error function, the proposed method maximizes the normalized variance sharpness function given by (7). Rather than computing the local visual features, the global image information is used in this work.…”

“…To overcome this problem, many works have used the iterative search approaches to find the best focus point [5], [6]. A Fourier transform-based autofocusing method is also presented in [7]. In order to provide a dynamic autofocus, a reliable and accurate method has to be developed.…”

The Weibull manifold in low-level image processing: An application to automatic image focusing

“…Such methods are usually based on the calculation of a "sharpness function" (SF), which is a real-valued estimate of the image focus. Commonly used sharpness functions in literature have been based on image derivatives [45,6,32,12,47,40], statistics [13,20,46,35,39] and Fourier transforms [24,44].…”