This article discusses the application of complex methods for detecting, recognizing, distinguishing borders and measuring various parameters of noisy, low-contrast, difficult-to-see images of space, air or ground objects. The problem of detecting, recognizing, distinguishing and measuring parameters of objects images (space or air objects, aircraft, ship, ground transport, people, coasts, etc.) is still among the very complex, completely unsolved radio engineering and telecommunications (“connected”) tasks. Currently, infrared (IR) direction finding, optical (laser location) direction finding and radar are used to detect, recognize, distinguish boundaries and measure the parameters of unknown objects against the background of external natural or artificial interference and noise. These methods have their own advantages and disadvantages, which do not always coincide. Therefore, it is of theoretical and practical interest to use them jointly, multifunctionally, or integrationally to identify objects against the background of external natural or deliberate interference and noise. When applying multifunctional methods for detecting, recognizing, distinguishing borders and measuring parameters of noisy, low-contrast images of objects against the background of external natural or artificial interference and noise. Digital processing of objects is mainly used now, which can be defined as a process during which an image is: modified to obtain a new one, which will be more convenient for research by a computer, or by the human eye; it is transformed into a certain set of characteristics and parameters visible and related to the observation area that are automatically analyzed by the computer, or directly presented to a person, taking into account pre-established criteria for developing a final conclusion about the studied object. Typically, the result of digital processing of the received signals is a new image that can be easily converted to analog form and directly observed on a computer display.
