• DocumentCode
    1944819
  • Title

    HMM-Based-Correlations in Infrared Remote-Image

  • Author

    Yang, Rui ; Li, Bo

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    There are plenty of correlations in infrared remote images that intensities of edge are as a regradually changed. As a result, infrared images usually seem to be blurry. Consequently,the correlations can be utilized to perform efficiently coding. The paper analyzed the characters of typical infrared remote-images. Based on HMM, the contextual model was founded to practice the bit plan e-coding. Within this method, innerstate of wavelet coefficients could be estimated according to its probabilistic character. Experiment results showed that the proposed algorithm was effective in infrared remote-image coding while the compression ratio was 16. And the PSNR can be improved by 0.3-1.2 dB. Moreover there is rarely visual distortion in reconstructed images. Meanwhile the method would have broader application prospects.
  • Keywords
    correlation methods; data compression; geophysical signal processing; hidden Markov models; image coding; image reconstruction; infrared imaging; remote sensing; wavelet transforms; HMM-based-correlations; bit plan e-coding; hidden Markov models; infrared remote-image coding; wavelet coefficients; Block codes; Computer science; Context modeling; Hidden Markov models; Image analysis; Image coding; Infrared imaging; Laboratories; Statistics; Wavelet coefficients; image compression; infrared image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.754
  • Filename
    4721676