Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2013, Vol. 10, No. 2, pp. 243-251

Hyperspectral images processing from aircraft and satellite vehicle-born carriers

V.N. Ostrikov 1, O.V. Plakhotnikov 1, A.V. Kirienko 2
1 LUCH Company, St. Petersburg branch
2 LUCH Company, St. Petersburg branch VEGA Radio Engineering Corporation, St. Petersburg branch
Рrocessing of hyperspectral images are considered. The preprocessing, external calibration and quality image estimation apply to remote sensing and synchronous surface measurements. Some methods of processing for detection and identification were used with the spectral data base utilize. The simulation model estimate the possibilities hyperspectral remote sensing devices on different observe conditions.
Keywords: гиперспектральная съемка, внешняя калибровка, предварительная, тематическая обработка, имитационное моделирование, hyperspectral images, external calibration, preprocessing, thematic processing, simulation modeling
Full text

References:

  1. Ostrikov V.N., Otsenka funktsii rasseyaniya tochki na proizvol'nom snimke posredstvom slepogo vosstanovleniya (Assessment of the scattering function of a point on a random shot through blind recovery), Tekhnicheskoe zrenie v sistemakh upravleniya (Technical vision systems management), Moscow: IKI RAN, 2012, pp. 16–20.
  2. Ostrikov V.N., Certificate of state patent for a computer program No. 2011616762, 31.08.2011. Official Bulletin of Rospatent, 2011.
  3. Ostrikov V.N., Plakhotnikov O.V., Certificate of state patent for a computer program No. 2011616765, 31.08.2011, Official Bulletin of Rospatent, 2011.
  4. Ostrikov V.N., Plakhotnikov O.V., Shulika K.M., Certificate of state patent for a computer program No. 2011616767, 31.08.2011, Official Bulletin of Rospatent, 2011.
  5. Ostrikov V.N., Plakhotnikov O.V., Shulika K.M., Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2012, Vol. 9, No. 2, pp. 167–172.
  6. Ostrikov V.N., Plakhotnikov O.V., Shulika K.M., Sobolev A.A., Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa: Tezisy dokladov VIII konferentsii (Current Problems in Remote Sensing of the Earth from Space: Abstracts of the VIII conference), Moscow: IKI RAN, 2010, pp. 14–15.
  7. Ostrikov V.N., Plakhotnikov O.V., Shulika K.M., Certificate of state registration of the computer program № 2011616764, 31.08.2011, Official Bulletin of Rospatent, 2011.
  8. Terebizh V.Yu., Vvedenie v statisticheskuyu teoriyu obratnykh zadach (Introduction to statistical theory of inverse problems), Moscow: Fizmatlit, 2005.
  9. Hyvarinen A., Oja E., Independent component analysis. Algorithms and applications, Neural Networks, 2000, No. 13 (4–5), pp. 411–430.