Decomposition of Spectral Features of Remote Sensing Based on the Correlation Coefficient Components

Abstract— A technique for decomposing the range of values of two-dimensional spectral features by the components of their constituent correlation coefficients has been proposed. The technique analyzes of the product of normalized values of spectral features. The feature used and user-defined thresholds for its values allow one to decompose initial statistical data and map the results obtained. Unlike traditional methods, the proposed approach has higher computational efficiency, which is necessary to process large amounts of statistical data. The results obtained from the application of the technique to processing remote sensing data of a natural object are considered.