Cognitive technologies for processing optical images of high spatial and spectral resolution


The main stages of the development of technologies for natural and anthropogenic object recognition (cognitive technologies for optical image processing) using remote sensing data are considered together with computational procedures for atmospheric correction of multispectral and hyperspectral air-space images. The main focus is on recognizing forest ecosystems of various species and age, based on inflight testing of domestic hyperspectral equipment for a selected test area, where ground-based forest inventory and other observations were carried out. High accuracies of the recognition of separate gradations of ages for the selected pure birch and pine stands are revealed using elaborated software for airborne hyperspectral image processing.

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Correspondence to V. V. Kozoderov.

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Original Russian Text © V.V. Kozoderov, E.V. Dmitriev, V.P. Kamentsev, 2014, published in Optika Atmosfery i Okeana.

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Kozoderov, V.V., Dmitriev, E.V. & Kamentsev, V.P. Cognitive technologies for processing optical images of high spatial and spectral resolution. Atmos Ocean Opt 27, 558–565 (2014).

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  • remote sensing
  • optical images
  • pattern recognition
  • forest canopies of various species and age