MINIMUM-ERROR-PROBABILITY RECEIVER FOR DETECTING A NOISY TARGET IN COLORED BACKGROUND-NOISE

We describe the design of an optimum receiver to detect a noisy target with unknown illumination in nonoverlapping colored background noise. The optimum receiver is designed on the basis of binary Bayesian hypo thesis testing with unknown parameters. Both white noise and colored n oise are considered to model the additive noise on the target. We show that the solution for the optimum receiver, when the additive noise i s white, consists of three terms: The first corresponds to the energy of the input signal, which is defined as the lexicographically ordered samples of the input image within the window of the reference; the se cond is the square of the correlation between the input signal and the energy-normalized reference; and the third corresponds to the energy of the whitened input signal. When the additive noise is colored, the third term is the same; however, the first two terms change such that the information in the correlation matrix of the additive noise is uti lized to process the input signal. (C) 1997 Optical Society of America .