A statistical signal processing approach to image fusion for concealed weapon detection

Abstract

A statistical signal processing approach to multisensor image fusion is presented for concealed weapon detection (CWD). This approach is based on an image formation model in which the sensor images are described as the true scene corrupted by additive non-Gaussian distortion. The expectation-maximization (EM) algorithm is used to estimate the model parameters and the fused image. We demonstrate the efficiency of this approach by applying this method to fusion of visual and non-visual images with emphasis on CWD applications.