Abstract
This paper proposes a method of detecting dynamic objects on an image from an optoelectronic device when there is a complex background formed by dense cumulus and altocumulus clouds. The image of the object is a small (point), low-contrast image. The fractal-correlation method is based on the use of a sample in the form of the ratio of the likelihood functions of close-by alternative situations of the type “only a complex background is observed in the viewing zone of the optoelectronic device” or “a dynamic object on a complex background is observed in the viewing zone of the optoelectronic device.” An algorithm is constructed for detecting a dynamic object as a binary accumulator, using the local, most powerful criterion. The critical limit for making a decision is determined according to the Neyman–Pearson lemma for the allowable false-detection probability of a dynamic object. Modelling is used to establish the high effectiveness of the method.
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