In order to realize real-time image fusion and improve fusion rate, an infrared and low-light image fusion algorithm based on wavelet transform is proposed, and an uncooled infrared and ICMOS image fusion system based on FPGA is developed on this paper. The system has completed image acquisition, image fusion and video output. Based on the analysis of the implementation of each part, this paper focuses on the study of image fusion algorithm based on FPGA. This algorithm greatly reduces the storage resources. At the same time, the fusion rule based on local energy is adopted to greatly improve the fusion effect of low-frequency images. The system can better retain the characteristics of infrared and low-light images which realize fusion imaging under 9* 10-4lx illumination. The experimental results show that the image processed by the proposed image fusion algorithm has good brightness characteristics, high contrast and large amount of information.
Since low-light-level images are generally grayscale images that lack color information, it is necessary to colorize these images to enhance human vision for night vision scene. In this paper, a low-light-level image colorization method is proposed based on Laws’ texture feature descriptor. Laws’ filter can analyze the texture features of the image, which are the pointers we used to find the corresponding color information for low-light-level gray images from the reference color image. The experimental results demonstrate that our colorization method can make night vision images have colors closer to natural perception and help observers better understand night vision scenes.
The process that the alpha particles emitted by the nuclear pollutants react with the nitrogen molecules in the air will produce ultraviolet photons with wavelengths of 280-390 nm, which can be detected by a photomultiplier tube. In this paper, a set of nuclear pollutant detection system based on photon counting detection system is designed. Firstly, the principle and development of nuclear pollution detectors and the development status of single photon detection technology are introduced. Then the overall system structure is introduced, the system is mainly composed of mechanical baffle, filter, photomultiplier, photon counter and upper computer software. The photon counter is composed of the preamplifier module, the signal discriminating circuit module and the pulse counting module. Finally, the detection experiment of the nuclear standard source is carried out, and the experimental results are analyzed. The analysis results show that the system can be used for the detection of nuclear pollutants in alpha particle sources.
Low-light-level (LLL) images, which are captured in the extreme environment without enough light for human eyes. LLL images quality degenerates badly with light decrease. The heavy noises and low contrast of the LLL images impede the access to the targets information. In order to enhance LLL images, we propose a two-step method to remove the complex noises. First, median filtering is adopted to remove the salt and pepper noises which are often introduced from the bad pixels. Second, the four-direction nonlocal means algorithm is adopted. The experimental results show that the proposed method can remove the noises and keep the details of the low illumination level scene effectively.
Microchannel plates (MCP) are devices that achieve electronic multiplication in the low-light intensifier system. MCP have the advantages of high gain, small size and light weight, being widely used in modern low-light, infrared, and ultraviolet image detection fields. In this paper, the fatigue and damage of MCP caused by strong input current are studied. The fatigue and damage of MCP are mainly reflected by the change of gain and body resistance. Experiments show that the gain of the MCP decreases under the condition of strong electron flow (2nA), and the body resistance decreases sharply after being damaged.