Infrared small target detection based on relevance vector regression

Abstract

It is the core task of space combat operations to detect and track targets, and the infrared target detection technology has an immediate impact on the performance of combat systems. So, the infrared target detection has been one of the emphases in military research. With the accelerated development of modern high-tech, combat systems are required more in their abilities of long-range target detection and tracking. It needs us to explore much more precise infrared target detection methods to achieve better target detection performance. To complete this challenging task, an infrared small target detection method based on Relevance Vector Regression (RVR) is proposed in this paper according to the characteristics of infrared target and related theories of RVR. Firstly, the basic theories and related techniques of RVR are introduced. Secondly, the specific method of infrared target detection based on RVR and nonlinear kernel correlation coefficient is reviewed. Thirdly, we proposed the new detection method based on RVR. In the last part, the experiment results which compared the new method with other methods are shown. The final experiment results prove that the proposed method has validity and better performance than the classical compared methods.