We investigated the effect of different gradient doping methods on the charge collection efficiency of the electron multiplication layer of Electron Bombarded CMOS (EBCMOS) devices. EBCMOS devices achieve high gain by bombarding the back side of the thinned sensor with photoelectrons. In order to improve the gain of EBCMOS devices, this paper obtains the multiplication process and scattering trajectory of electrons in the electron multiplication layer of EBCMOS from the Monte-Carlo statistical method, combined with the interaction model of low-energy electrons and P-type silicon substrate, and finally calculates the charge collection efficiency under different doping methods. It is demonstrated experimentally that a suitable doping method can improve the charge collection efficiency of EBCMOS devices, thus improving the imaging quality. The optimized doping structure model achieves a charge collection efficiency of 94.18% at an incident electron energy of 4 KeV, an incident electron beam diameter of 20 nm, and a P-type epitaxial layer of 10 um.
In this paper, starting from the noise and blur characteristics of the strain clamp X-ray image , an image processing method combining bilateral filter denoising and unsharp mask enhancement is proposed. Experimental results show that unsharp mask algorithm have certain limitations in image edge enhancement. After the image is denoised by bilateral filtering,the unsharp mask method is used for image edge enhancement, which can effectively expand the scope of the unsharp mask algorithm. This method greatly improve the image qualityand help identify defects. It provides a strong guarantee and support for the X-ray inspection of the strain clamp, and has important practical value.
The electron-multiplying charge-coupled device (EMCCD) is widely used in low-light-level (LLL) imaging field. In order to solve the problems of low signal-to-noise ratio (SNR) and low contrast of EMCCD LLL images under low illumination, a denoising method based on the nonlinear diffusion filter with wavelet transform and contrast sensitivity function (CSF) is proposed. Aiming at the problems existing in the P-M diffusion model, that is, the diffusion coefficient is easily disturbed by noise, and the direction affects the noise reduction process, the method introduces the wavelet transform and the CSF, then a new diffusion function is proposed to reduce the noise of LLL images. The experimental results show that, compared with other denoising methods, the proposed method has better denoising effect on EMCCD LLL images.
In this paper, a method of removing ion-feedback noise based on RPCA and median filter is proposed, a removal mechanism based on iterative strategy of "detection-location-removal" is established to remove the noise step by step, and BM3D algorithm is used to remove the Gaussian noise. The experimental results show that the proposed method can effectively remove the noise, and protect the edges and details of ICCD LLL images as much as possible. In addition, we quantitatively evaluate the denoising performance of the method. Our method obtains better objective measurement values. It has better effectiveness and robustness for ICCD LLL image denoising.
KEYWORDS: Spatial frequencies, Imaging systems, Target recognition, Signal to noise ratio, Convolutional neural networks, Detection and tracking algorithms, Neural networks, Image processing, Modulation transfer functions, Human vision and color perception
A new objective measurement method of minimum resolvable contrast (MRC) based on convolutional neural network (CNN) is proposed in this paper, in view of the fact that the subjective measurement results are easily affected by the observer’s subjectivity. Due to the low signal-to-noise ratio (SNR) of the low-light-level (LLL) images, it is difficult for traditional recognition algorithms to achieve ideal results, but the CNN can automatically learn features from the sample data for image recognition. This method does not depend on subjective judgment. It uses neural network instead of human eyes to recognize low SNR LLL images with different spatial frequencies and contrasts. The experimental results show that CNN is accurate and reliable, MRC images can be effectively recognized by it. The objective measurement of MRC based on CNN has good stability.
According to the interaction model between low-energy electrons and solids, combined with Monte Carlo calculation method, MATLAB software was used to simulate the electron scattering trajectories of a large number of photoelectrons incident on EBCMOS substrates. The energy loss rate of different incident photoelectrons on the substrate was analyzed. The influence of electron incidence depth and the range of electron motion. When the incident photoelectron energy increases, the energy loss rate gradually decreases, and the electron incident depth and the electron motion range increase. The simulation results can provide reference and basis for the design and preparation of the back-illuminated CMOS device substrate.
With the demand for back-illuminated CMOS/CCD and electron bombardment imaging devices, the requirement for chip thickness has become the key to various imaging device fabrication techniques. In this paper, the back of semiconductor silicon wafer was thinned by means of mechanical grinding and wet etching. The thinned chip was tested by the step meter and atomic force microscope. The chip thinning technology realizes the thickness of 15 μm, which provides technical support for the preparation of backlight imaging devices or electron bombardment imaging devices.
The change of heavy metal content in water environment, soil and plant can reflect the change of heavy metal pollution in ecological environment, and it is important to monitor the trend of heavy metal pollution in eco-environment by using water environment, soil and heavy metal content in plant. However, the content of heavy metals in nature is very low, the background elements of water environment, soil and plant samples are complex, and there are many interfering factors in the EDXRF system that will affect the spectral analysis results and reduce the detection accuracy. Through the contrastive analysis of several heavy metal elements detection methods, it is concluded that the EDXRF method is superior to other chemical methods in testing accuracy and method feasibility when the heavy metal pollution in soil is tested in ecological environment.
In order to improve the imaging quality of X-ray and reduce the effects of X-ray and scatter line on image, the adoption
of X-ray collimator is the most effective method. MCP collimator in parallel structure can effectively reduce the ratio of
X-ray and scatter line to reach on image plane, and reduce the atomization degree of images, so as to improve the image
contrast. Through the establishment first-order radiation transmittance model of MCP collimator, test the performance of
MCP collimator, it is prove that the MCP collimator can be used in the imaging system that consists of proximity of
X-ray image intensifier, first-order radiation transmittance calculation formula of MCP absorption type collimator in
parallel structure is reduced, obtain the transmittance distribution non cosine curve distribution of MCP collimator
through calculating.
In the proximity of X-ray imaging systems based on X-ray image intensifier, pixel matching and noise suppression are
important methods to improve image quality. This paper analyzes CCD parameters’ impact on imaging quality and the
relations with, proposes pixel matching degree is a critical factor to restrict the performance of imaging system, and
verified by experiments, the CCD refrigeration can effectively suppress the image noise, which adopts the extension of
integration time method and obtains favorable signal-to-noise ratio, it also provides a simple and low cost solution for
high quality X-ray real-time imaging of static objects.
KEYWORDS: X-rays, Real time imaging, X-ray imaging, Imaging systems, Modulation transfer functions, Image quality, Spatial frequencies, Image processing, Monte Carlo methods, Computer simulations
In order to improve the performance of X ray geometric imaging, the key factors of size and image of X ray focus and
geometric clarity as well as imaging quality of real time imaging system were studied by using software simulation.
Analyze the reasons and factors that affecting the X - ray focus size and blurred image, evaluated the performance of X
ray geometric imaging through the relationship between the relationship of X-ray focus size and image geometric
definition. It provides a low cost and high efficiency solution for the selection of X-ray tube in the system design.
Based on the imaging features of the original image intensifier of X-ray, the light halo caused by X-ray projective halation is analyzed, the result shows the stray X-ray energy is lower than the direct X-ray energy. The screen brightness generated by the image intensifier of X-ray stimulated by the stray X-ray energy is weaker than that generated by the direct X-ray energy. In addition the projector facula reflected from the direct X-ray is focused on the central region of X-ray image intensifier, therefore a toroidal ring similar to the solar halation is formed around the projector halation. The results of the theoretical analysis and experimental discovery show this phenomenon caused by X-ray tube on X-ray image intensifier can not be eliminated and in the system of X-ray size detection composed of them the X-ray halation will reduce the detection accuracy resulting in measurement results’ deviation dispersion under given conditions. This kind of nonlinear system error can not be canceled out by the segmented modification of coefficient compensation but it can be restrained through the adjustment of correction coefficients. After the physical testing and comparison of the physical normal size the accuracy of 0.1mm of the compensated X-ray measurement results after the adjustment of correction coefficient has been reached. The results are highly reproducible and the method of the segmented coefficient compensation has been improved.
KEYWORDS: Ions, Electrons, Signal to noise ratio, Image intensifiers, Monte Carlo methods, Interference (communication), Microchannel plates, Night vision, Scattering, Image quality
To analyze the effect of ion barrier film in micro-channel plate on the performance of proximity focusing low-light-level
image intensifier, the noise characteristics of ion barrier film are studied. The transmission electrons’ distribution for
those have transmitted ion barrier films is determined by simulating the collision interaction between the incident
electrons and ion barrier film with Monte Carlo method. Furthermore, the relationship model of the incident electrons
and transmission electrons are established by time differential method. We simulate how the incident electron energy and
ion barrier film thickness affect the noise factor of ion barrier film. The simulation analysis results reveal that the noise
factors gradually decreased with the increase of incident electron energy (0.1 KeV - 2.0 KeV) and decreasing of film
thickness (1 to 8 nm). So the tendency of simulation results is accordant with the actual devices. The smaller noise factor
means the better image quality for low-light-level image device, and the simulation results suggest how to realize the ion
barrier film in low light level image intensifier with low noise factor. Therefore, the study of ion barrier film’s noise
characteristics provides theoretical and technical support for optimization of the
three generations low-light-level device’s performance.
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