A new non‐linear pseudo‐Laplacian filter for enhancement of secondary electron images

Oho, Eisaku; Ogihara, Akinori; Kanaya, K.

doi:10.1111/j.1365-2818.1990.tb03016.x

Cited by 11 publications

(4 citation statements)

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“…When combined with digital image processing, the digitally recorded SEM images provide some additional options. Algorithms for enhancement of edges and local contrast as well as suppression of noise ( Oho et al ., 1984 , 1986, 1987, 1990) allow important image structures to be emphasized ( Fig. 3).…”

Section: Resultsmentioning

confidence: 99%

“…Compared to conventional photographs, digital images of SEM data allow digital filtering for noise reduction, edge enhancement, etc. ( Oho et al ., 1990 ; Oho & Peters, 1994) and superior control of contrast and gradation curve ( Oho, 1992), and provide data sets ideal for automated morphometry and image analysis ( Martin et al ., 1985 ; Holmes et al ., 1987 ).…”

Section: Introductionmentioning

confidence: 99%

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A simple method for the acquisition of high‐quality digital images from analog scanning electron microscopes

Gebert

Preiss

1998

Journal of Microscopy

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A method is described for converting video signals of analog scanning electron microscopes (SEMs) into digital images of high quality. A plug-in card commercially available for personal computers is used for the on-line analog/digital conversion. A Windows application program written by the authors, together with low-level software drivers supplied with the plug-in card, allow digital images to be recorded, to be displayed simultaneously on the computer monitor and to be saved as a file in a standardized format. Compared to conventional photographic images obtained from the SEM camera system, the digital images possess superior sharpness of outline, excellent image definition, diminished noise and well-defined grey-scale tones. This method provides SEM images of high quality for less than $1000 from most older analog SEMs. In addition, the advantages of digital image processing can be applied to analog SEMs, including contrast enhancement, digital filtering and multichannel recording.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A simple method for the acquisition of high‐quality digital images from analog scanning electron microscopes

Gebert

Preiss

1998

Journal of Microscopy

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“…Many noise removal techniques have been introduced to enhance the quality of images corrupted by noise, but because of some characteristics of different techniques, for example, dependency on image structure, presence of different processing parameters, and degradation of image important details, they can only be used in some special fields. Several different noise reduction approaches have been proposed in SEM field (Herzog et al ., ; Yew and Pease, ; Lewis and Sakrison, ; Oron and Gilbert, ; Jones and Smith, ; Oho et al ., , ; Yano and Nomura, ; Sim et al ., , , ; Kiani et al ., ). Different filters use various approaches to achieve this aim.…”

Section: Introductionmentioning

confidence: 99%

Suppression of noise in SEM images using weighted local hysteresis smoothing filter

Mazhari

Hasanzadeh

2016

Scanning

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It has been proven that Hysteresis Smoothing (HS) has several advantages for Scanning Electron Microscopy (SEM) image noise reduction. HS uses hysteresis thresholding to remove noise besides preserving important details of images. Determination of optimal threshold values (cursor width) plays an effective role in improving the performance of HS based filters. Recently, a novel local technique, named Local Adaptive Hysteresis Smoothing (LAHS), has been proposed to compute an optimal cursor width. In this paper, a new method is proposed to improve the performance of LAHS in noise reduction and detail preservation. In the proposed approach which is based on weighted averaging, local statistical characteristics of the image are used in order to modify the final values of estimated pixels by LAHS method. Proposed method is applied to SEM images corrupted by different levels of noise. Noise reduction and detail preservation performance of the proposed method is compared in both objective and subjective manners with other HS based filters. Experimental results demonstrate that the proposed method is successful in improving the performance of LAHS and also it achieves better performance in noise reduction besides detail preservation of SEM images in comparison with other HS based filters. SCANNING 38:634-643, 2016. © 2016 Wiley Periodicals, Inc.

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“…Many techniques for noise removal using digital image processing were introduced to the SEM field (Herzog et al, ; Yew and Peace, ; Lewis and Sakrison, ; Oron and Gilbert, ; Jones and Smith, ; Oho et al, , ; Yano and Nomura, ; Sim et al, ). However, since we have to usually submit to the side effects of noise removal processing, that is, the degradation of important information (processing artifacts), only a few techniques are effectively utilized in many commercial SEMs.…”

Section: Introductionmentioning

confidence: 99%

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

Suzuki

Oho

2012

SCA

Self Cite

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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.

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A new non‐linear pseudo‐Laplacian filter for enhancement of secondary electron images

Cited by 11 publications

References 10 publications

A simple method for the acquisition of high‐quality digital images from analog scanning electron microscopes

A simple method for the acquisition of high‐quality digital images from analog scanning electron microscopes

Suppression of noise in SEM images using weighted local hysteresis smoothing filter

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

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