In the process of crack identification for round logs, conventional edge extraction cannot effectively suppress noise because of the tree's annual ring lines and the similarity between the burr noises during cutting and the gray level of the target. Therefore, it is no easy to extract the target crack. The method of continuous gray-scale transformation enhancement is put forward in this thesis to increase the difference between the gray level of the background pixel and the gray level of the target so that can obtain an ideal pre-processed image. In the process of image preprocessing, the method of continuous gray-scale transformation enhancement is applied, that is to combine the gray-scale transformation enhancement and the non-linear filtering process so that can realize the preprocessing of the original image. The gray level difference between the extraction target and the background is increasing under the premise of preserving the image-extraction features. In the extraction process, the extracted target crack image is obtained through utilizing the localization minimum in mathematical morphology and then the compound morphological algorithm is designed based on the basic algorithm of mathematic morphology so as to obtain the target crack image which is connected by the edge curves. Results The MATLAB image processing algorithm is used to simulate each step of the method. The results show that the extracted target crack images are ideal. The mentioned algorit can not only ensure the integrity of the extraction target, but also can suppress the noise very well so that can satisfy the needs during the extraction of complex background images, especially the images with little difference between the background gray level and the extraction target gray level.
Luminance gain is an important parameter to evaluate the light intensity enhancement ability of the low light level image intensifier assembly. The higher the luminance gain, the easier the receiver is to sense and recognize. However, luminance gain is not a directly measurable physical quantity. Thus, luminance gain measuring devices have non-standard specific properties. Based on the principle of luminance gain measuring specified in the standard, the structure and measurement methods of measurement devices are analyzed, the error and optimization methods of two major measurement methods are compared, and the distribution of the combined uncertainty of measuring luminance gain is studied. Then, an optimized measurement scheme of luminance gain of low light level image intensifier assembly is put forward. Based on this scheme, a comprehensive measurement uncertainty analysis is carried out and the calculated luminance gain measurement extended combined uncertainty is about 6.7% (k=2). The results are of great significance for improving the measurement accuracy of luminance gain of low light level image intensifier assembly.
The MCP current gain of low-light-level image intensifier is an important indicator for evaluating the detection characteristics of low-light-level image intensifier, and it is essential to achieve accurate measurement. In this paper, the method and device for measuring the MCP current gain of the micro-light image intensifier are established. The process of measuring the magnitude and the influencing factors when measuring the MCP current gain of low-light image intensifier, and the measurement uncertainty of the device is carried out. The MCP current gain measurement has an extended uncertainty of 5.27%. It can meet the requirements of high precision measurement of MCP current gain. of low-light-level image intensifier. The research results are used to assist in the development of low-light-level image intensifier technology, providing an effective and accurate detection method for further improvement and improvement of its technical performance.
Effective harvesting light is a key factor for photoelectrical device to enhance quantum efficiency and responsitivity. Periodic nano structure has been proved and fabricated to harvest more light based on complex lithography and low efficiency e-beam lithography.Thereby, a cost-effective method of using PS sphere as hard mask was suggested to prepare sub-micro nano pillar on silicon surface as anti-reflective films.Field distribution of nano silicon pillar were simulated in FDTD software and simulation results showed that anti-reflective could be modified by changing the silicon diameter and period. The simulation results show that the center wavelength of the high-reflection film moves with the change of the nano pillar period, and the reflection intensity changes with the diameter and length of the nano pillar. Silicon nano pillar with 180nm diameter and 520nm period was determined theoretically and experimentally to be as anti-reflective films covering wavelength from 601nm to 640nm with average reflectance of less than 5%.
Images often suffer from low visibility under nonuniform illumination, weak luminance and backlight environment. This paper describes a novel approach to improvement the visualization of poor light conditions. Firstly, we raise the global brightness using an adaptive exponent induced function. To enhance the local detail perception, the local contrast is boosted by contrast preserving which utilizes human vision system model. To not bias from original image, we generate the contrast combined original image and global illuminance enhance output in the gradient domain. To reduce artifacts, the guided filter is employed to estimate the local mean illuminance when transform the contrast. The experimental results demonstrate that our proposed method has a pleasant visual effect and low computational complexity than the state of the arts.
Fixed pattern noise (FPN) in infrared images seriously degrades the imaging quality and visual effect of infrared focal plane arrays (FPAs). Although many scene-based non-uniformity correction (NUC) algorithms have been developed recent years, the convergence speed of the bias and gain correction parameters still need to be further improved. In this paper, we present a novel NUC approach for IR FPAs which minimizes the total variation of the estimated IR irradiance guided by a noise model image, and we name it guided total variation (GTV) NUC method. A temporal detection factor is introduced to NUC procedure to prevent NU parameters updating when scene movement stops. In the proposed scheme, the correction parameters of the FPN are estimated via an iterative optimization strategy, frame by frame. The experimental results of synthetic and real IR videos demonstrate that the proposed algorithm have better NUC performance in terms of fewer ghosting artifacts and faster convergence than the state-of-the-art methods.
The radiation gain of UV image intensifier is an important index to measure response capability of ultraviolet detector, thus its accurate measurement is necessary. This paper establishes radiation gain measurement method and device of ultraviolet image intensifier, The process of measuring the magnitude and Influencing factors for the measurement of ultraviolet radiation gain by the equipment were analyzed. And the error analysis of the measurement uncertainty of the device, The radiation gain measurement has an extended uncertainty of 9.59%, It can meet the requirements of high precision measurement of radiation gain of UV image intensifier. The research achievement can support the research and development of domestic ultraviolet detectors, thus providing an effective and accurate detection method for improving and promoting the technical performance of ultraviolet detectors.
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