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Forms of images and indication of targets

Targets usually have relatively steady geometrical forms. Backgrounds are characterized by uncontrollable variations of brightness. Those characterizations are taken into account in the model of the form of targets and in the model of background. If all the models are randomized, then we can distinguish the targets by an effective principle of the maximum likelihood of distinction. If the model of the geometrical form of the targets is deterministic and the background is an additive gaussian noise, then the morphological principle of distinction of the targets is effective. The distinction of targets is not effective in Cartesian space, for example at inverting brightness of the images of targets on a uniform background. In systems of radio-vision it is necessary to account into consideration the antenna pattern for effective distinction of targets. The local-linear method of super-resolution is included in the distinction and indication problems. The main idea of the new super-resolution method is in the resolving function. The local resolving functions are steady calculated in the local domains where antenna pattern is defined. The local resolving functions save the mean brightness' in the local domains. This property can be used in order to suppress the uncontrollable background. These and other questions are considered in the report by using examples of the model images of targets and backgrounds.