Research On Infrared Image Target Detection And Tracking

Nowadays, with the development of high-tech weapon, a kind of weapon system based on infrared detection becomes one of the key studying and developing projects in various countries. Infrared target detection and tracking technology is always the bottleneck problem that affects the performance of infrared equipment, and the problem must be solved urgently. The research and analysis on this problem is proposed deeply and extensively in this paper. The research content mainly includes the infrared dim target detection, infrared image moving target detection, infrared global motion estimation and infrared target tracking technology.According to the different awareness between infrared target and background edge with different structuring elements, an infrared dim target fusion detection method based on multiple structuring elements background estimation is proposed in this paper. Firstly, this method processes the infrared image using Top-Hat with four linear structuring elements. Secondly, this method fuses the first step result using multiplication to stand the object out of the background. Finally, this method detects the target using adaptive threshold segmentation. This method overcomes the bad picture compatibility of the traditional method based on single structuring element, and this method has good performance in goat enhancement and background suppression.A method of infrared image moving target detection in a complex environment is proposed in this paper according to the request of infrared system. This method fuses the frame subtraction method and the background subtraction method. Firstly, this method matches background and makes the motion compensation, and then the motion region based on frame difference can be obtained. Secondly, by comparing with the multi-frames motion region, this method reconstructs the background when the motion region has no overlaps. Finally, the target can be detected by background subtraction method. Thecomplete mdtion target can be detected with this method.A method of global motion estimation based on RANSAC+LS algorithm is proposed in this paper. Firstly, this method previews the matching block and then acquires enough inliers using RANSAC algorithm, secondly, it estimates the global motion estimation parameter using LS algorithm. This method has high efficiency and this method uses inliers as many as possible compared with traditional RANSAC algorithm, and it can overcome traditional LS algorithm's disadvantage. This paper compares RANSAC+LS algorithm with LS estimation method, M estimation method, LMedS algorithm and RANSAC algorithm. The simulation result shows that the RANSAC+LS algorithm has better performance than traditional algorithms.To solve the target tracking problem in non-linear and non-gaussion noise, an infrared target tracking method based on UPF algorithm is proposed in this paper. This method generates proposal distributions using UKF instead of the transition prior p(x_k|x_k-1) as the proposal distribution. Comparing with traditional PF algorithm, this method solves the degeneracy and overcomes the disadvantage when choose the p(x_k|x_k-1) as the proposal distribution. Experiments are done to compare the performance of the four algorithms: UPF, EKF, UKF, and PF, and the results shows that the new particle filter outperforms obviously the standard particle filter and other filters such as EKF and UKF. This method is used in infrared image tracking.In summary, the infrared target detection and tracking problems are researched in this paper, and new algorithms have been proposed. The experimental results indicate that the algorithms can get better results in the target detection and tracking field.