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Book ChapterDOI

Adaptive Threshold Processing of Secondary Electron Images in Scanning Electron Microscope

08 Aug 2019-pp 166-173
TL;DR: It is concluded from a large number of tests that when the secondary electron image gray histogram has obvious double peaks and is located in the trough, the threshold obtained is optimal and it is possible to better observe the pictures under the SEM.
Abstract: Observing the sample under a scanning electron microscope (SEM) requires adjustment of brightness and contrast to obtain a clear image. The traditional method is manually adjusted by the operator, which inevitably has errors. In this paper, an adaptive threshold processing method based on image-based normalized gray histogram is proposed. This method can acquire the threshold of the image according to the state of the currently obtained secondary electron images. When the brightness and contrast of the image change, the threshold can also be changed accordingly. It is concluded from a large number of tests that when the secondary electron image gray histogram has obvious double peaks and is located in the trough, the threshold obtained is optimal. Therefore, it is possible to better observe the pictures under the SEM.
References
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BookDOI
01 Jan 1985

3,322 citations

Journal ArticleDOI
01 Aug 2002-Polymer
TL;DR: In this article, a novel image processing method was developed to extract interfacial area concentration measurements from 2D micrographs of immiscible polymer blends for analyzing scanning electron microscopy (SEM) images.

65 citations

Journal ArticleDOI
TL;DR: In this paper, a survey of image contrasts in scanning electron microscopy is presented, where simplified considerations in the physics of the secondary electron emission yield, δ, are combined with the effects of a partial collection of the emitted secondary electrons.
Abstract: Image formation in scanning electron microscopy (SEM) is a combination of physical processes, electron emissions from the sample, and of a technical process related to the detection of a fraction of these electrons. For the present survey of image contrasts in SEM, simplified considerations in the physics of the secondary electron emission yield, δ, are combined with the effects of a partial collection of the emitted secondary electrons. Although some consideration is initially given to the architecture of modern SEM, the main attention is devoted to the material contrasts with the respective roles of the sub-surface and surface compositions of the sample, as well as with the roles of the field effects in the vacuum gap. The recent trends of energy filtering in normal SEM and the reduction of the incident energy to a few electron volts in very low-energy electron microscopy are also considered. For an understanding by the SEM community, the mathematical expressions are explained with simple physical arguments.

54 citations

Journal ArticleDOI
01 Apr 2017-Sensors
TL;DR: The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons and shows the similar accuracy and the availability in all seasons.
Abstract: Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions.

29 citations

Journal ArticleDOI
TL;DR: This work compared the multi-observation fusion performance to threshold-based methods, proposed for the assessment of the therapeutic response based on functional volumes, and demonstrated improved and more robust estimation of the evaluation leading to more pertinent measurements.
Abstract: In positron emission tomography (PET) imaging, an early therapeutic response is usually characterized by variations of semi-quantitative parameters restricted to maximum SUV measured in PET scans during the treatment. Such measurements do not reflect overall tumor volume and radiotracer uptake variations. The proposed approach is based on multi-observation image analysis for merging several PET acquisitions to assess tumor metabolic volume and uptake variations. The fusion algorithm is based on iterative estimation using a stochastic expectation maximization (SEM) algorithm. The proposed method was applied to simulated and clinical follow-up PET images. We compared the multi-observation fusion performance to threshold-based methods, proposed for the assessment of the therapeutic response based on functional volumes. On simulated datasets the adaptive threshold applied independently on both images led to higher errors than the ASEM fusion and on clinical datasets it failed to provide coherent measurements for four patients out of seven due to aberrant delineations. The ASEM method demonstrated improved and more robust estimation of the evaluation leading to more pertinent measurements. Future work will consist in extending the methodology and applying it to clinical multi-tracer datasets in order to evaluate its potential impact on the biological tumor volume definition for radiotherapy applications.

12 citations