Abstract

The urgent problem of remote sensing information analysis is to form the most adequate statements, that is, hypotheses with the highest values of probability of their realization. The paper deals with the problem of combining and ranking hypotheses with interval estimates of their probability under conditions of uncertainty, the application of which will allow to estimate the states of the objects of interest in remotely sensed image. A numerical example is used to illustrate proposed method.

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