Some digital image processing problem types, such as sorting, reference comparison, classification, remote sensing, monitoring and quickest adaptive detection of image "disorders" are dealt with. Principal fundamental problems to be solved here are: 1) selection of informative features, and 2) as full as possible extraction of useful information out of data and its effective use. A solution approach is suggested for the above problems, based on the concept of invariant "coupling" of unknown parameters by some data functions, and integration or summation for these invariant "couplings". Here, on the one hand, it appears possible to derive a synthesis procedure for effective statistical decision rules which are not strictly dominated by any other decision rules with respect to specified loss functions, and, on the other hand, the decision rules per se are readily implementable on digital computers. Some new results have been obtained, showing the highest effectivity to be achieved when handling small data volumes. Several examples are presented.