Research And Implementation Of Enhancement Algorithms For Images Of Shooting Range

With the rapid development of the new weapons, modern shooting range, as an effective means of testing weapons and a spot of providing crucial data, needs to speed up the scene contruction of visualization, informatization and modernization. Optical equipment is an important part of identifying and testing in the shooting range, of which, Photoelectric Theodolite(PT) is to fast capture, stably track and guide image data in real time. There are two kinds of heterologous imaging sensors to shoot ground targets and aerial targets in the PT. They are infrared visible imaging systems, respectively. Visible imaging system is able to capture high-resolution, clear targets, and gain the trace and flight attitude, providing rich and reliable test data to a land-based command facility. But, visible imaging system is susceptible to atmospheric jitter, rain, snow and other natural weather factors. If the moving target is obscured by clouds and mist, visible imaging system can not complete the capturing targets. Finally, target is lost; if the moving target’s color is close to sky, it is unable to identify the target location. Visible imaging system can not shoot targets for precision measurement.In recent years, infrared technology has anti-interference ability and strong penetrating power, much higher range and all weather operations. It becomes the core technology, widely applied in the military. Due to the diffraction of infrared imaging system, the resolution of the infrared image is much lower than visible image. Detecting distant targets and moving target occupys small size in the target surface. The pixels of target concentrated in a small range of gray level range. The infrared images have a small dynamic range, low contrast, and fuzzy phenomenon. When the interference from external environment and the presence of imperfect imaging system, resulting in the presence of noise, low SNR, likely to be submerged in the background. Infrared images are imaged according to its radiation characteristics, the visual effect is far less visible images, and not easier to observe for the human eye. Hence, improving image quality is the key issue to improve the system performance of PT.In this paper, based on characteristics for the shooting range images, the research on image enhancement algorithms is proposed with needs of national defense and military projects. Aiming at improving infrared image contrast, signal to noise ratio and visual effects perspective, the task is firstly on the basis of in-depth analysis of domestic and international researching status of image enhancement algorithm, and progress of the above, For low contrast and blurred edges of the problem, a novel enhancement method of adaptive platform histogram equalization is proposed. Fuzzy enhancement method is based on logarithmic membership about fuzzy set. For the problem of low signal to noise ratio,lateral inhibition network enhancement model is established from the perspective of Human Visual Characteristics(HVC); meanwhile,it is combined with adaptice filtering method for smoothing target noise. Adding compensation measure factor is de-noising image blur. To improve the visual effect and meet the demands of human visual perception, the image fusion combined with the fuzzy set theory and statistical characteristics is proposed for enhancing. The enhanced images based on fusion technology not only can improve the shortcomings of a singlesensor, but also improve the efficiency of image information. Meanwhile, the design of hardware platform is based on FPGA + DSP processor of image enhancement system. Transplanting the enhancement algorithms, there is a number of experimental tests to verify the correctness and feasibility of image enhancement algorithms and hardware platform system solutions.