Computer-aided detection and classification method for concealed targets in hyperspectral imagery

Detecting concealed targets in an unknown environment presents a great challenge in hyperspectral image analysis since the prior knowledge about targets, the background and environment is not available. In this paper, a computer-aided detection and classification method (CADCM) for concealed targets is proposed. It is fully computer-automated and requires no a priori information at all. It consists of three successive processes: (1) a band selection procedure; (2) a band rationing approach; and (3) an automatic target detection and classification algorithm (ATDCA). The effectiveness of the proposed CADCM is evaluated by HYperspectral Digital Imagery Collection Experiment (HYDICE) image scenes. The results show that targets which are concealed by shade, natural background or covered by man-made objects can be effectively detected and further classified by CADCM.