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.
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.
The intensified charge-coupled device (ICCD) is widely used in the field of low-light-level (LLL) imaging. The LLL images captured by ICCD suffer from low spatial resolution and contrast, and the target details can hardly be recognized. Super-resolution (SR) reconstruction of LLL images captured by ICCDs is a challenging issue. The dispersion in the double-proximity-focused image intensifier is the main factor that leads to a reduction in image resolution and contrast. We divide the integration time into subintervals that are short enough to get photon images, so the overlapping effect and overstacking effect of dispersion can be eliminated. We propose an SR reconstruction algorithm based on iterative projection photon localization. In the iterative process, the photon image is sliced by projection planes, and photons are screened under the constraints of regularity. The accurate position information of the incident photons in the reconstructed SR image is obtained by the weighted centroids calculation. The experimental results show that the spatial resolution and contrast of our SR image are significantly improved.
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.
Based on the technology of tunable diode laser absorption spectroscopy, modulation of the center wavelength of 2004 nm distributed feedback laser diode at a room-temperature, the second harmonic amplitude of CO2 at 2004nm can be obtained. The CO2 concentration can be calculated via the Beer-Lambert law. Sinusoidal modulation parameter is an important factor that affects the sensitivity and accuracy of the system, through the research on the relationship between sinusoidal modulation signal frequency, amplitude and Second harmonic linetype, we finally achieve the detection limit of 10ppm under 12 m optical path.
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