To quickly obtain a 3D model of real world objects, multi-point ranging is very important. However, the traditional measuring method usually adopts the principle of point by point or line by line measurement, which is too slow and of poor efficiency. In the paper, a no scanning depth imaging system based on TOF (time of flight) was proposed. The system is composed of light source circuit, special infrared image sensor module, processor and controller of image data, data cache circuit, communication circuit, and so on. According to the working principle of the TOF measurement, image sequence was collected by the high-speed CMOS sensor, and the distance information was obtained by identifying phase difference, and the amplitude image was also calculated. Experiments were conducted and the experimental results show that the depth imaging system can achieve no scanning depth imaging function with good performance.
Image fusion technology usually combines information from multiple images of the same scene into a single image so that the fused image is often more informative than any source image. Considering the characteristics of low-light visible images, this study presents an image fusion technology to improve contrast of low-light images. This study proposes an adaptive threshold-based fusion rule. Threshold is related to the brightness distribution of original images. Then, the fusion of low-frequency coefficients is determined by threshold. Pulse-coupled neural networks (PCNN)-based fusion rule is proposed for fusion of high-frequency coefficients. Firing times of PCNN reflect the amount of detail information. Thus, a high-frequency coefficient corresponding to maximum firing times is chosen as the fused coefficient. Experimental results demonstrate that the proposed method obtains high-contrast images and outperforms traditional fusion approaches on image quality.
Due to the effect of bad weather conditions, it often conducts visual distortions on images for outdoor vision systems.
Rain is one specific example of bad weather. Generally, rain streak is small and falls at high velocity. Traditional rain
removal methods often cause blued visual effect. In addition, there is high time complexity. Moreover, some rain streaks
are still in the de-rained image. Based on the characteristics of rain streak, a novel rain removal technology is proposed.
The proposed method is not only removing the rain streak effectively, but also retaining much detail information. The
experiments show that the proposed method outperform traditional rain removal methods. It can be widely used in
intelligent traffic, civilian surveillance and national security so on.
Proc. SPIE. 9521, Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics 2014, Part I
KEYWORDS: Digital signal processing, Fiber optic gyroscopes, Image processing, Video, Image resolution, Field programmable gate arrays, Linear filtering, Video surveillance, Image transmission, Video processing
As the effect of atmospheric particles scattering, the video image captured by outdoor surveillance system has low contrast and brightness, which directly affects the application value of the system. The traditional defogging technology is mostly studied by software for the defogging algorithms of the single frame image. Moreover, the algorithms have large computation and high time complexity. Then, the defogging technology of video image based on Digital Signal Processing (DSP) has the problem of complex peripheral circuit. It can’t be realized in real-time processing, and it’s hard to debug and upgrade. In this paper, with the improved dark channel prior algorithm, we propose a kind of defogging technology of video image based on Field Programmable Gate Array (FPGA). Compared to the traditional defogging methods, the video image with high resolution can be processed in real-time. Furthermore, the function modules of the system have been designed by hardware description language. At last, the results show that the defogging system based on FPGA can process the video image with minimum resolution of 640×480 in real-time. After defogging, the brightness and contrast of video image are improved effectively. Therefore, the defogging technology proposed in the paper has a great variety of applications including aviation, forest fire prevention, national security and other important surveillance.