EMD Based Infrared Image Target Detection Method
- PDF / 230,590 Bytes
- 11 Pages / 439.37 x 666.142 pts Page_size
- 80 Downloads / 286 Views
EMD Based Infrared Image Target Detection Method He Deng & Jianguo Liu & Hong Li
Received: 12 September 2008 / Accepted: 30 June 2009 / Published online: 11 July 2009 # Springer Science + Business Media, LLC 2009
Abstract Under the complicated background of infrared image, the small target detection is a vital challenging task in modern military. In order to solve this problem, a novel method based on the empirical mode decomposition (EMD) is proposed in the paper, to detect small targets under complicated sea-sky background. The detection process contains two steps: the first step is to suppress the sea-sky background of the infrared image based on EMD; the second step is to segment the target from the background suppressed image through a threshold. The application of infrared images has shown that the performance of the algorithm can detect infrared small target under sea-sky background exactly. Compared with wavelet transformation, the testing results based on EMD method achieve tantamount results wavelet transformation, and even better in some respects. The simulations show that EMD method presented in this paper appears instructive for both theoretical and practical points of view. Keywords Small target detection . Infrared image . Background suppression . Threshold . EMD
1 Introduction Under the complicated background of infrared image, the small target detection, identification and tracking applications in modern military are vital challenging tasks. It has been researching for many years on infrared imaging systems and automatic target detection [1].The complexity of this problem arises when the target is small, faint and partially obscured by surrounding objects, embedded in clutters. In these complex H. Deng (*) : J. J. G. LiuLiu Institute for Pattern Recognition & Artificial Intelligence, Huazhong University of Science and Technology, Wuhan 430074, People’s Republic of China e-mail: [email protected] H. Li Institute for Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, People’s Republic of China
1206
J Infrared Milli Terahz Waves (2009) 30:1205–1215
situations, the features of both the target and the background are generally nonseparable in the original image space. It is difficult for those detection algorithms to work in the original image space. So, the image has to be transformed into a so-called feature space, in which those features can be separated. Since targets and clutters have different spatial frequency characteristics, a spatial filter could be designed to suppress and detect targets. Bhanu and Jones summarized a lot of algorithms for automatic target detection in static infrared images that were developed up to the early 1990s [2].These algorithms predominately utilize traditional image-processing approaches for optical pictures processing. Recently, the wavelet transformation has emerged as an excellent methodology for small targets detection because it gives a lot of advantages among all other image-processing techniques. Simply speaking, in sm
Data Loading...
