Abstract: The article reviews algorithmic support of multispectral video systems in the part of automatic selection of the most informative channels, which are video sensors of different spectral ranges, forming images of different informativeness depending on weather conditions. Such systems can be used to increase the awareness of aircraft pilots or operators of unmanned aerial vehicles in difficult weather conditions. The usage of these algorithms is considered using the example of airborne systems of improved (enhanced) vision where it is necessary to give the pilot a single combined image of the external situation, due to the limited space of the information-control field of the cockpit and the increased requirements for decision-making. The development and research was carried out using the base of video sequences obtained in the course of real flight experiments of the prototype of a three-channel video system as well as expert judgment on the consistency of the results of the work of algorithms with visual perception. The study is the further development of image analysis algorithms in terms of their informativeness. The article proposes a new adaptive algorithm for automatic selection of individual video channels for their subsequent integration based on the information-free metric of informativity. The proposed automatic calculation of the priority of video channels for informativeness showed its consistency with the subjective perception of useful information by the human operator.

Abstract: The subject of the research is the algorithms for evaluating the information value of composite images. Composite images are formed by multispectral vision systems including multispectral enhanced vision systems used in aviation. These systems show the external space for pilots even in bad weather conditions or late at night, thus increasing operational capacities of aerial vehicles. These systems combine information incoming from physically different sensors into one composite image that is supposed to have essential information features coming from all combined video channels. The research is b ased on the computer modeling of image combination in the two-zone TV-thermal enhanced vision system using the actual images made by the visual sensors. The authors offer a new structural-semantic qualitative evaluation of the information value of composite images based on the preservation (distortion) of various information depending on their spectral energy and space characteristics. Based on the aforesaid method of evaluating the information value, the authors compare different methods of combination of images for the two-zone enhanced vision systems.