Technology for Fundamental Improvement of an Extremely Low-Quality Video Signal for Use in Fine Focusing and Astigmatism Correction in Scanning Electron Microscopy.

This study describes important techniques for production of a series of video signals for use in fine focusing operations and near-perfect astigmatism correction in the general-purpose scanning electron microscopy (SEM) field. These techniques can enhance the stability of the signal greatly when used for focusing. As two particularly important fundamental techniques, SEM image acquisition with priority given to the signal-to-noise ratio and signal reinforcement based on the active image processing concept were utilized fully. The performance improvement was evaluated using the case of a previously reported support system for fine focusing and astigmatism correction based on image covariance. The method is almost completely robust against noise within practical limits and allows for focusing and astigmatism correction for even extremely noisy SEM images. The results of this study may be useful not only in the SEM field but also in many fields that use weak signals.

Highly Reliable Method to Obtain a Correlation Coefficient Unaffected by the SEM Noise Component for Examining the Degree of Specimen Damage due to Electron Beam Irradiation.

A correlation coefficient is often used as a measure of the strength of a linear relationship (i.e., the degree of similarity) between two sets of data in a variety of fields. However, in the field of scanning electron microscopy (SEM), it is frequently difficult to properly use the correlation coefficient because SEM images generally include severe noise, which affects the measurement of this coefficient. The current study describes a method of obtaining a correlation coefficient that is unaffected by SEM noise in principle. This correlation coefficient is obtained from a total of four SEM images, comprising two sets of two images with identical views, by calculating several covariance values. Numerical experiments confirm that the measured correlation coefficients obtained using the proposed method for noisy images are equal to those for noise-free images. Furthermore, the present method can be combined with a highly accurate and noise-robust position alignment as needed. As one application, we show that it is possible to immediately examine the degree of specimen damage due to electron beam irradiation during a certain SEM observation, which has been difficult until now.

Applying Fast Scanning Method Coupled with Digital Image Processing Technology as Standard Acquisition Mode for Scanning Electron Microscopy.

This study proposes an efficient and fast method of scanning (e.g., television (TV) scan) coupled with digital image processing technology to replace the conventional slow-scan mode as a standard model of acquisition for general-purpose scanning electron microscopy (SEM). SEM images obtained using the proposed method had the same quality in terms of sharpness and noise as slow-scan images, and it was able to suppress the adverse effects of charging in a full-vacuum condition, which is a challenging problem in this area. Two problems needed to be solved in designing the proposed method. One was suitable compensation in image quality using the inverse filter based on characteristics of the frequency of a TV-scan image, and the other to devise an accurate technique of image integration (noise suppression), the position alignment of which is robust against noise. This involved using the image montage technique and estimating the number of images needed for the integration. The final result of our TV-scan mode was compared with the slow-scan image as well as the conventional TV-scan image.

Support system for fine focusing and astigmatism correction using an auditory signal in scanning electron microscopy.

The current study describes a new support system for fine focusing and near-perfect astigmatism correction for scanning electron microscopy (SEM). The signal-to-noise ratio of a series of SEM images obtained from fast scan rates (TV scan) was adopted as a new metric for evaluating focus. Measured signal-to-noise ratio values were converted to an acoustic signal (sound wave frequency) using digital image processing techniques, enabling the SEM user to evaluate image focus using the auditory modality. Accurate focusing and correcting astigmatism in general-purpose SEM is traditionally time-consuming and difficult. The proposed system may substantially reduce the required operation time for fine focusing. Moreover, the system is relatively immune to noise, successfully supporting focus and astigmatism correction with very noisy SEM images. Our proposed focus support system may be helpful for general-purpose SEM observation of a variety of specimens under a wide range of operating conditions.

Special raster scanning for reduction of charging effects in scanning electron microscopy.

A special raster scanning (SRS) method for reduction of charging effects is developed for the field of SEM. Both a conventional fast scan (horizontal direction) and an unusual scan (vertical direction) are adopted for acquiring raw data consisting of many sub-images. These data are converted to a proper SEM image using digital image processing techniques. About sharpness of the image and reduction of charging effects, the SRS is compared with the conventional fast scan (with frame-averaging) and the conventional slow scan. Experimental results show the effectiveness of SRS images. By a successful combination of the proposed scanning method and low accelerating voltage (LV)-SEMs, it is expected that higher-quality SEM images can be more easily acquired by the considerable reduction of charging effects, while maintaining the resolution.

Feature evaluation of complex hysteresis smoothing and its practical applications to noisy SEM images.

Quality of a scanning electron microscopy (SEM) image is strongly influenced by noise. This is a fundamental drawback of the SEM instrument. Complex hysteresis smoothing (CHS) has been previously developed for noise removal of SEM images. This noise removal is performed by monitoring and processing properly the amplitude of the SEM signal. As it stands now, CHS may not be so utilized, though it has several advantages for SEM. For example, the resolution of image processed by CHS is basically equal to that of the original image. In order to find wide application of the CHS method in microscopy, the feature of CHS, which has not been so clarified until now is evaluated correctly. As the application of the result obtained by the feature evaluation, cursor width (CW), which is the sole processing parameter of CHS, is determined more properly using standard deviation of noise Nσ. In addition, disadvantage that CHS cannot remove the noise with excessively large amplitude is improved by a certain postprocessing. CHS is successfully applicable to SEM images with various noise amplitudes.

Highly accurate SNR measurement using the covariance of two SEM images with the identical view.

Quality of an SEM image is strongly influenced by the extent of noise. As a well-known method in the field of SEM, the covariance is applied to measure the signal-to-noise ratio (SNR). This method has potential ability for highly accurate measurement of the SNR, which is hardly known until now. If the precautions discussed in this article are adopted, that method can demonstrate its real ability. These precautions are strongly related to "proper acquisition of two images with the identical view," "alignment of an aperture diaphragm," "reduction of charging phenomena," "elimination of particular noises," and "accurate focusing," As necessary, characteristics in SEM signal and noise are investigated from a few standpoints. When using the maximum performance of this measurement, SNR of many SEM images obtained in a variety of the SEM operating conditions and specimens can be measured accurately.

Image restoration for TV-scan moving images acquired through a semiconductor backscattered electron detector.

A semiconductor backscattered electron (BSE) detector has become popular in scanning electron microscopy session. However, detectors of semiconductor type have a serious disadvantage on the frequency characteristics. As a result, fast scan (e.g. TV-scan) BSE image should be blurred remarkably. It is the purpose of this study to restore this degradation by using digital image processing technology. In order to improve it practically, we have to settle several problems, such as noise, undesirable processing artifacts, and ease of use. Image processing techniques in an impromptu manner like a conventional mask processing are unhelpful for this study, because a complicated degradation of output signal affects severely the phase response as well as the amplitude response of our SEM system. Hence, based on the characteristics of an SEM signal obtained from the semiconductor BSE detector, a proper inverse filter in Fourier domain is designed successfully. Finally, the inverse filter is converted to a special convolution mask, which is skillfully designed, and applied for TV-scan moving BSE images. The improved BSE image is very effective in the work for finding important objects.

Quality improvement of environmental secondary electron detector signal using helium gas in variable pressure scanning electron microscopy.

The quality of the image signal obtained from the environmental secondary electron detector (ESED) employed in a variable pressure (VP) SEM can be dramatically improved by using helium gas. The signal-to-noise ratio (SNR) increases gradually in the range of the pressures that can be used in our modified SEM. This method is especially useful in low-voltage VP SEM as well as in a variety of SEM operating conditions, because helium gas can more or less maintain the amount of unscattered primary electrons. In order to measure the SNR precisely, a digital scan generator system for obtaining two images with identical views is employed as a precondition.

An improved scanning method based on characteristics of the human visual system for scanning electron microscopy.

An improved scanning method for the scanning electron microscope (SEM) is proposed. Here, quincuncial scanning (sampling) instead of a conventional (raster) scanning is used. This scanning method is very effective for quality improvement of an SEM image obtained under undersampling conditions (rough sampling). The present study focuses on characteristics of the human visual system, specifically the low response of eyes in diagonal directions. When using this method coupled with a high-precision interpolation, the number of pixels necessarily doubles. It is not surprising that it is advantageous for printing. A more important advantage is the fact that SEM images can be acquired with a shorter recording time. Hence, this type of scanning will be helpful for quick and frequent recordings in a "snapshot" mode, which up to now has not been achieved successfully by SEM.

Mechanical scanning of the specimen in the scanning electron microscope.

A scanning electron microscope (SEM) system equipped with a motor drive specimen stage fully controlled with a personal computer (PC) has been utilized for obtaining ultralow magnification SEM images. This modem motor drive stage works as a mechanical scanning device. To produce ultra-low magnification SEM images, we use a successful combination of the mechanical scanning, electronic scanning, and digital image processing techniques. This new method is extremely labor and time saving for ultra-low magnification and wide-area observation. The option of ultra-low magnification observation (while maintaining the original SEM functions and performance) is important during a scanning electron microscopy session.

Reduction in acquisition time of scanning electron microscopy image using complex hysteresis smoothing.

Complex hysteresis smoothing (CHS), which was developed for noise removal of scanning electron microscopy (SEM) images some years ago, is utilized in acquisition of an SEM image. When using CHS together, recording time can be reduced without problems by about one-third under the condition of SEM signal with a comparatively high signal-to-noise ratio (SNR). We do not recognize artificiality in a CHS-filtered image, because it has some advantages, that is, no degradation of resolution, only one easily chosen processing parameter (this parameter can be fixed and used in this study), and no processing artifacts. This originates in the fact that its criterion for distinguishing noise depends simply on the amplitude of the SEM signal. The automation of reduction in acquisition time is not difficult, because CHS successfully works for almost all varieties of SEM images with a fairly high SNR.

Metrics for focusing in extremely noisy scanning electron microscopy condition.

Finding a best focused image in very noisy condition is an extremely difficult task for the SEM user. If a performance, which is much higher than that of an expert in focusing, can be achieved in a computer-controlled scanning electron microscope (SEM), it will be very helpful for our field due to the many possible applications. To accomplish this work, we employ a powerful metric-the covariance obtained by a special scanning method. It can select the best focused image from a series of SEM images acquired by altering the focus of the objective lens under an extremely noisy SEM image condition. The noise immunity of the present method is quantitatively evaluated, and it is further improved based on the obtained evaluation result.