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Analysis of Bayes mathematical systems of pattern recognition for identifying the objects on hyperspectral photographs

The objective of this paper is the analysis of Bayes mathematical systems of pattern recognition for identifying the objects on hyperspectral photographs. The analysis of statistical characteristics of pattern recognition models according to Bayes criterion we used as the primary research method. In the paper we considered three basic mathematical models, among which were used the criteria of Bayes, Neumann-Pearson and the minimax criterion. This paper presents findings upon practicability of these models for identifying the objects on hyperspectral photographs with application of vegetative indexes. By the results of the research we concluded that for establishing the mathematical model of the system of pattern recognition on hyperspectral photographs a research is required upon probabilistic characteristics of the distribution of vegetation indices for specific objects of the underlying surface. Consequently, developing a centralized database of spectral characteristics is required.