Optimal processors for images with an arbitrary number of gray levels

We present a new group of processors, optimal in a maximum-likelihood sense, for target location in images with a discrete number of gray levels. The discrete gray-level distribution can be of any arbitrary form. We compare the performance of the processor derived for five discrete levels with the performance of a processor derived for a continuous Gaussian distribution and show that there are cases when only the processor derived for discrete levels will exhibit satisfactory performance. We give an explanation of this difference based on moment analysis and show how the correlation orders are related to statistical moments of the input scene.