Automation and Remote Control

, Volume 62, Issue 10, pp 1688–1697 | Cite as

On Quasiholographic Coding of Digital Images

  • A. V. Markovskii


A method of distributed coding of digital images was proposed in imitation of the holographic principle of image recording. It allows one to regenerate images with appreciable losses of their surface. Consideration was given to the variants of distributed coding and decoding of images. A method of interpolation-based regeneration of defective images was described.


Mechanical Engineer Digital Image System Theory Image Recording Holographic Principle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Stroke, G.W., An Introduction to Coherent Optics and Holography, New York: Academic, 1966. Translated under the title Vvedenie v kogerentnuyu optiku i golografiyu, Moscow: Mir, 1967.Google Scholar
  2. 2.
    Gabor, D., Associative Holographical Memories, IBM J. Res. Develop., 1969, vol. 13, no. 2, pp. 156–159.Google Scholar
  3. 3.
    Pribram, K.H., Nuwer, M., and Baron, R.J., The Holographic Hypothesis of Memory Structure in Brain Function and Perception, in Contemporary Developments in Mathematical Psychology (V.II), Kranz, D.H., Atkinson, R.C., Luce, R.D., and Suppes, P., Eds., San Francisco: Freeman, 1974.Google Scholar
  4. 4.
    Heanue, F., Bashaw, M.C., and Hesselink, L., Volume Holographic Storage and Retrieval of Digital Data, Science, 1994, vol. 265, p. 749.Google Scholar
  5. 5.
    Psaltis, D. and Burr, G.W., Holographic Data Storage, Computer, 1998, vol. 31, no. 2, pp. 52–60.Google Scholar
  6. 6.
    Ashley, J., Holographic Data Storage, IBM J. Res. Develop., 2000, vol. 44, no. 3, pp. 341–349.Google Scholar
  7. 7.
    Kuznetsov, O.P., Holographic Models of Data Processing in Neuron Networks, Dokl. Ross. Akad. Nauk, 1992, vol. 324, no. 3, pp. 537–540.Google Scholar
  8. 8.
    Kuznetsov, O.P., Nonclassical Paradigms in Artificial Intelligence, Teor. Sist. Upravlen., 1995, no. 5, pp. 3–23.Google Scholar
  9. 9.
    Kuznetsov, O.P., Pseudoopticcal Neuron Networks: Rectilineal Models, Avtom. Telemekh., 1996, no. 12, pp. 145–154.Google Scholar
  10. 10.
    Kuznetsov, O.P and Shipilina, L.B., Pseudoopticcal Neuron Networks: Complete Rectilineal Model and Methods of Calculation of its Behavior, Teor. Sist. Upravlen., 2000, no. 5, pp. 168–176.Google Scholar
  11. 11.
    Yaroslavskii, L.P. and Merzlyakov, N.S., Tsifrovaya golografiya (Digital Holography), Moscow: Nauka, 1982.Google Scholar
  12. 12.
    Yaroslavskii, L.P. and Merzlyakov, N.S., Metody tsifrofoi golografii (Methods of the Digital Holography), Moscow: Nauka, 1977.Google Scholar
  13. 13.
    Swan T., Inside Windows File Formats, Indianapolis: Sams Pub., 1993. Translated under the title Formaty failov Windows, Moscow: Binom, 1995.Google Scholar
  14. 14.
    Knuth, D.E., The Art of Computer Programming. Vol. 2 Seminumerical Algorithms, Reading: Addison-Wesley, 1969. Translated under the title Iskusstvo programmirovaniya. Tom 2. Poluchislennye algoritmy, Moscow: Vil'yams, 2000.Google Scholar

Copyright information

© MAIK “Nauka/Interperiodica” 2001

Authors and Affiliations

  • A. V. Markovskii
    • 1
  1. 1.Trapeznikov Institute of Control SciencesRussian Academy of SciencesMoscowRussia

Personalised recommendations