Dim target detection based on nonlinear multifeature fusion by Karhunen-Loeve transform

Abstract

Dim target detection and tracking is a key technique for imaging tracking systems and is a challenging and leading-edge subject. A new strategy for dim target detection is presented. Various nonlinear features that are representative of dim targets are extracted from image sequences. Then, an information fusion algorithm by Karhunen-Loeve (K-L) transform is used to obtain an integrated feature. As a correlation degree, using an integrated feature calculates a target's position coordinates. Experimental results demonstrate the proposed method is feasible and effective.