Abstract
The problem of forming images that are optimal with respect to a Mean Square Error (MSE) criterion, based on nite data, is considered. First, it is shown that the MSE criterion is consistent with the general goal of classifying images, in that decreasing the MSE guarantees a decrease in the probability of misclassifying an image. The problem of choosing sampling locations for image formation that optimize the MSE is then formulated. It is shown that this MSE minimization problem has a solution under certain conditions and necessary conditions for a minimum are obtained. The results are illustrated on a simple image formation problem.
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