Research On Infrared Target Detection And Tracking Technology Based On Lifting Wavelet Transform

Infrared imaging technology as an emerging technology has been widely applied in military and civilian. But low contrast and the drawback of noise pollution restricted its deep-step application. Therefore, the processing of infrared images is particularly important.Infrared small target detection and tracking as an area of infrared image processing has aroused the attention and research of the world. An important factor to determine the outcome of modern war lies in how we can detect and track enemy targets as far as possible to fight in the most favorable time to attack. For this reason, the study of small target detection and tracking algorithm have great significance in improving the range of the infrared imaging system. This paper based on lifting wavelet transform theory and a further study of infrared small target detection and tracking algorithm. The main contents are as follows.The purpose of infrared image preprocessing is to eliminate the impact of clutter. First of all, there is a description of the preprocessing algorithm in commonly use, and then we make the comparison of the application of wavelet analysis and NSCT in image enhancement. On this account, we raise the image preprocessing algorithm which combined lifting wavelet and NSCT. And the effect of pretreatment in using this algorithm is well, which lays the foundation for further work.During the process of infrared small target detection. The energy of infrared small targets is usually relatively weak relatively and susceptible to noise interference that often bring a lot of trouble to the detection. Based on lifting wavelet to do the difference processing of image, this paper get a better detection result by using PCNN infrared target detection.Because the infrared small target lack of particularly Hing-like structure and characteristic information, it is difficult to establish better mathematical model. In order to achieve better tracking results in this paper, we use the particle filtering technique which results are relatively good to track infrared small targets. The final trajectory chart of view show that the algorithm can perform well in tracking the targets.