ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2011, Vol. 8, No. 3, pp. 55-63

Computational aspects of classificators construction with different complexity using hyperspectral airspace imagery processing

V.V. Kozoderov 1, E.V. Dmitriev 2, V.D. Egorov 2, V.V Borzyak 1
1 M.V.Lomonosov Moscow State University
2 Institute of Numerical Mathematics of Russian Academy of Sciences
Results of georeferenced hyperspectral and air photo imagery are considered for classification of natural and anthropogenic objects. Main attention is paid to computational aspects of the area contours separation for the objects within a scene under processing. The smoke from forest fires, sources of the fires as well as the forest vegetation areas without the fires and smoke are filled in the contours. Characteristic features of the spectra for the objects under study and their variability within the selected contours are shown using hyperspectral airborne data processing.
Keywords: hyperspectral airspace imagery, data processing, spectra analysis
Full text


  1. Kozoderov V.V., Dmitriev E.V., Issledovanie Zemli iz kosmosa, 2010, No. 1, pp. 69-86.
  2. Kozoderov V.V., Kondranin T.V., Raikunov G.G., Kazantsev O.Yu., Belotserkovskii A.V., Astashkin A.A., Bobylev V.I., Dmitriev E.V., Kamentsev V.P., Borzyak V.V., Shcherbakov M.V., Lesunovskii A.A., Issledovanie Zemli iz kosmosa, 2010, No. 5, pp. 59-68.
  3. Dalponte M., Bruzzone L., Vescovo L., Gianelle D., The role of spectral resolution and classifier
  4. complexity in the analysis of hyperspectral images of forest areas, Remote Sensing of Environment, 2009, Vol. 113, pp. 2345-2355.
  5. Foody G.M., Mathur A., Toward intelligent training of supervised image classifications: Directing training data acquisition for SVM classification, Remote Sensing of Environment, 2004, Vol. 93, pp. 107-117.
  6. Jain A.K., Duin R.P.W., Mao J., Statistical Pattern Recognition: A Review, IEEE Transactions on pattern analysis and machine intelligence, 2000, Vol. 22, No. 1, pp. 4-37.
  7. Plaza A., Benediktsson J.A., Boardman J.W., Brazile J., Bruzzone L., Camps-Valls G., Chanussot J., Fauvel M., Gamba P., Gualtieri A., Marconcini M., Tilton J.C., Trianni G., Recent advances in techniques for hyperspectral image processing, Remote Sensing of Environment, 2009, Vol. 113, pp. 110-122.