MINIMUM-MEAN-SQUARE-ERROR FILTERS FOR DETECTING A NOISY TARGET IN BACKGROUND-NOISE

A minimum-mean-square-error filter is proposed to detect a noisy targe t in spatially nonoverlapping background noise. In this model, both th e background noise that is spatially nonoverlapping with the target an d the noise that is additive to the target and the input image are con sidered. The criterion used to design the filter is to minimize the me an-square-error between the filter output and a delta function located at the target position in the presence of the noise. Computer-simulat ion results for a number of noisy input images are presented, and the performance of the filter is determined. We also Bst the filter discri mination against undesired objects and tolerance to target distortions , such as rotation End scaling. (C) 1996 Optical Society of America