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Indian Journal of Physics

, Volume 92, Issue 4, pp 417–421 | Cite as

Analysis of identification of digital images from a map of cosmic microwaves

  • J. Skeivalas
  • V. TurlaEmail author
  • M. Jurevicius
  • G. Viselga
Original Paper

Abstract

This paper discusses identification of digital images from the cosmic microwave background radiation map formed according to the data of the European Space Agency “Planck” telescope by applying covariance functions and wavelet theory. The estimates of covariance functions of two digital images or single images are calculated according to the random functions formed of the digital images in the form of pixel vectors. The estimates of pixel vectors are formed on expansion of the pixel arrays of the digital images by a single vector. When the scale of a digital image is varied, the frequencies of single-pixel color waves remain constant and the procedure for calculation of covariance functions is not affected. For identification of the images, the RGB format spectrum has been applied. The impact of RGB spectrum components and the color tensor on the estimates of covariance functions was analyzed. The identity of digital images is assessed according to the changes in the values of the correlation coefficients in a certain range of values by applying the developed computer program.

Keywords

Planck microwave map Digital images Identification Covariance function 

PACS Nos.

02.50.Fz 05.45-a 06.30.-k 13.85.Tp 95.55.Br95.55.-n 

References

  1. [1]
    Smoot Group The cosmic microwave background radiation Lawrence Berkeley Laboratory (Retrieved 2008)Google Scholar
  2. [2]
    P Noterdaeme, P Petitjean, R Srianand, C Ledoux and S López Astron. Astrophys. 526 L7 (2011). arXiv:1012.3164, Bibcode: 2011A&A…526L…7 N,  https://doi.org/10.1051/0004-6361/201016140
  3. [3]
    D Hanson et al Phys. Rev. Lett. 111(14) (2013). arXiv:1307.5830, Bibcode: 2013PhRvL, 111n1301H,  https://doi.org/10.1103/physrevlett.111.141301
  4. [4]
    W Clavin NASA Technology Views Birth of the Universe (Washington: NASA) (Retrieved March 17, 2014)Google Scholar
  5. [5]
    D Overbye The New York Times (Retrieved March 17, 2014)Google Scholar
  6. [6]
    Planck Collaboration Team Astron. Astrophys. (September 19, 2014). arXiv:1409.5738
  7. [7]
    N Cardoulas, A C Bird and A I Lawan Photogramm. Eng. Remote Sens. 62(10) 1173 (1996)Google Scholar
  8. [8]
    M Ekstrom and A McEwen Photogramm. Eng. Remote Sens. 56(4) 453 (1990)ADSGoogle Scholar
  9. [9]
    G Horgan Photogramm. Eng. Remote Sens. 64(12) 1171 (1998)Google Scholar
  10. [10]
    B Hunt, T W Ryan and F A Gifford Photogramm. Eng. Remote Sens. 59(7) 1161 (1993)Google Scholar
  11. [11]
    J P Antoine Revista Ciencias Matematicas (La Habana) 18 113 (2000)Google Scholar
  12. [12]
    D E Dutkay and P E T Jorgensen Revista Matemática Iberoamericana 22 131 (2004)Google Scholar
  13. [13]
    J Skeivalas Theory and Practice of GPS Networks (Vilnius: Technika) (2008)Google Scholar
  14. [14]
    J Skeivalas and R Kizlaitis Geod. Cartogr. 35(2) 50 (2009)ADSCrossRefGoogle Scholar
  15. [15]
    J Skeivalas and E Parseliunas Opt. Eng. 52(7) (2013)Google Scholar

Copyright information

© Indian Association for the Cultivation of Science 2017

Authors and Affiliations

  • J. Skeivalas
    • 1
  • V. Turla
    • 2
    Email author
  • M. Jurevicius
    • 3
  • G. Viselga
    • 3
  1. 1.Department of Geodesy and CadastreVilnius Gediminas Technical UniversityVilniusLithuania
  2. 2.Department of Printing MachinesVilnius Gediminas Technical UniversityVilniusLithuania
  3. 3.Department of Mechanical EngineeringVilnius Gediminas Technical UniversityVilniusLithuania

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