doi: 10.17586/2226-1494-2016-16-2-258-264


ANALYSIS OF CAMOUFLAGE COVER SPECTRAL CHARACTERISTICS BY IMAGING SPECTROMETER

A. Y. Kouznetsov, S. S. Sergeev


Read the full article  ';
Article in Russian

For citation: Kouznetsov A.Yu., Sergeev S.S. Analysis of camouflage cover spectral characteristics by imaging spectrometer. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2016, vol. 16, no. 2, pp. 258–264. doi:10.17586/2226-1494-2016-16-2-258-264

Abstract

 Subject of Research.The paper deals with the problems of detection and identification of objects in hyperspectral imagery. The possibility of object type determination by statistical methods is demonstrated. The possibility of spectral image application for its data type identification is considered. Method. Researching was done by means of videospectral equipment for objects detection at "Fregat" substrate. The postprocessing of hyperspectral information was done with the use of math model of pattern recognition system. The vegetation indexes TCHVI (Three-Channel Vegetation Index) and NDVI (Normalized Difference Vegetation Index) were applied for quality control of object recognition. Neumann-Pearson criterion was offered as a tool for determination of objects differences. Main Results. We have carried out analysis of the spectral characteristics of summer-typecamouflage cover (Germany). We have calculated the density distribution of vegetation indexes. We have obtained statistical characteristics needed for creation of mathematical model for pattern recognition system. We have shown the applicability of vegetation indices for detection of summer camouflage cover on averdure background. We have presented mathematical model of object recognition based on Neumann-Pearson criterion. Practical Relevance. The results may be useful for specialists in the field of hyperspectral data processing for surface state monitoring.


Keywords: imaging spectrometer, hyperspectral image, vegetation index, remote sensing, camouflage coating

References

1. Dobrolensky Y.S., Krasavtsev V.M., Kuznetsov A.Y., Chikov K.N. The use of off-axis paraboloid mirror as a promising input lens ozonometer. Proc. Int. Congress on Intelligent Systems and Information Technology, IS&IT. Taganrog, Russia, 2013, pp. 352–357.
2. Feng C., Anees A. Design and modeling of a compact imaging spectrometer. Optical Engineering, 1995, vol. 34, no. 11, pp. 3217–3221.
3. Nouri H., Beecham S., Hassanli A.M., Kazemi F. Water requirements of urban landscape plants: a comparison of three factor-based approaches. Ecological Engineering, 2013, vol. 57, pp. 276–284. doi: 10.1016/j.ecoleng.2013.04.025
4. De Benedetto D., Castrignanò A., Rinaldi M., Ruggieri S., Santoro F., Figorito B., Gualano S., Diacono M., Tamborrino R. An approach for delineating homogeneous zones by using multi-sensor data. Geoderma, 2013, vol. 199, pp. 117–127. doi: 10.1016/j.geoderma.2012.08.028
5. Abrams L., Alberotanza L., Cavalli R.M. et. al. Satellite and airborne remote sensing data study the Venice lagoon. Proc. 5th Int. Airborne Remote Sensing Conference and Exhibition. San Francisco, 2001, art. 132.
6. Shilin B.V., Gruzdev V.N., Markov A.V., Mochalov V.F. Using spectral aerial imaging for ecological monitoring. Journal of Optical Technology, 2001, vol. 68, no. 12, pp. 900–907.
7. Brovkina O.V., Grigor'eva O.V., Gruzdev V.N., Zakharov S.V., Ponomarev S.A., Chapurskii L.I., Chikov K.N. Equipment, methods and results of the materials usage in videospectral and thermal aerial surveys for environmental monitoring of land and water areas. Current Problems in Remote Sensing of the Earth from Space, 2007, vol. 4, no. 1, pp. 209–215. (In Russian)
8. Chikov K.N., Gud V.V., Krasavtsev V.M. Onboard videospectral complex for geological and environmental mapping. Nauchnye Issledovaniya Vysshei Shkoly po Ekologii i Ratsional'nomu Prirodopol'zovaniyu. Sb. Statei [Research at Higher School of Ecology and Environmental Management. Articles Collection]. St. Petersburg, SPbMI Publ., 2000, pp. 173–175. (In Russian)
9. Kuzmin A.K., Chikov K.N. Perspective panoramic auroral imager and its opportunities for tomographic mapping and diagnostics of ionospherical characteristics from the satellite. Advances in Space Research, 2003, vol. 31, no. 5, pp. 1321–1326. doi: 10.1016/S0273-1177(02)00946-8
10. Chikov K.N., Gud V.V., Krasavtsev V.M. Development of vdeospectral bases of aerospace methods for remote sensing in the optical range. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2005, no. 7 (23), pp. 64–73.
11. Kozoderov V.V., Kondranin T.V., Dmitriev E.V. Subject Processing of Multispectral and Hyperspectral Space Images. Moscow, MFTI Publ., 2013, 224 p. (In Russian)
12. Kuznetsov A.Yu. Processing methods for hyperspectral data. Sbornik Tezisov Dokladov Kongressa Molodykh Uchenykh. Vypusk 1 [Abstracts of the Young Scientists Congress. Issue 1]. St. Petersburg, NIU ITMO Publ., 2013, pp. 96–97.
13. Chapurskii L.I., Alekseev A.A., Astakhova E.I. et. al. Experience in using a prism videospektrometra "Lepton" to measure the reflection properties of the target elements of the terrestrial test environment. Sbornik Tezisov Dokladov Konferentsii "Giperspektral'nye Pribory i Tekhnologii" [Proc. Conf. on Hyperspectral Instruments and Technologies]. Krasnogorsk, Russia, 2013, pp. 99–100. (In Russian)
14. Gorelik A.L., Skripkin V.A. Metody Raspoznavaniya [Recognition Methods]. Moscow, Vysshaya Shkola Publ., 1977, 222 p.
15. Palazov K.I., Bochev Al.Z., Spaso St., Manev A., Kuzmin Al.K., Stepanov Vl.A., Eysmont N.A., Prohorenko V.I., Chikov K.N., Auroral phenomena as seen by coordinated measurements of SKA-3, UVSIPS and IMAP-3 experiments on board the INTERBALL-2 satellite. Advances in Space Research, 2003, vol. 31, no. 5, pp. 1341–1346. doi: 10.1016/S0273-1177(03)00017-6
16. Artyukhina N.K., Kotov M.N. Features of construction remote sensing imaging spectrometers from space. Devices and Methods of Measurements, 2010, no. 1, pp. 56–62.
17. Nouri H., Beecham S., Anderson S., Nagler P. High spatial resolution WorldView-2 imagery for mapping NDVI and its relationship to temporal urban landscape evapotranspiration factors. Remote Sensing, 2014, vol. 6, no. 1, pp. 580–602. doi: 10.3390/rs6010580
 



Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Copyright 2001-2021 ©
Scientific and Technical Journal
of Information Technologies, Mechanics and Optics.
All rights reserved.

Яндекс.Метрика