Detection And Tracking Small Target In Infrared Sequence Images

Small targets detection in infrared image is one of the key techniques of infrared search and track system, making use of infrared image to realize the automatic target examination, recognition and tracking is the main development direction in equipments of modern military weapons. Because infrared sensor is easily affected by atmosphere hot radiation, long distance and sensor noise, the detected targets in infrared images often present like dim targets, even like point targets, and drowned in noise. The small targets detection in infrared images is one of the key techniques in military weapon system. Have become important factors to decide the victory or defeat of modern warfare.The longer and the distance of target, the less imaging area of target, and the larger probabilities of targets influenced by backgrounds and clutter, comparing with other topics in the field of detection and tracking, the small targets can be robustly detected and tracked under complex backgrounds have become the more realistic and challenging research topics. Detecting and tracking algorithm of moving small targets in IR images with complex background are investigated in this dissertation. The main work can be summarized on image preprocessing, target detection and tracking. Detection before tracking algorithm idea is simple and direct because use single frame after preprocessing using morphological operation, in real-time performance is better, test results. I used on my work DBT with different methods of thresholding.The condensation filter has gained prominence in the area of target tracking because it is robust to non-linear target motion and non-Gaussian additive noise. Traditional track filters, such as the Kalman filter, have been well studied for linear tracking applications, but perform poorly for non-linear applications. The condensation filter has been shown to perform well in non-linear applications. The condensation filter method is computationally intensive and advances in processor speed and computational power have allowed this method to be implemented in tracking applications. This thesis explores the use of the condensation filter to track small target in noisy imagery. And compare the result with Kalman filter.