• DocumentCode
    2955822
  • Title

    Hyperspectral image compression through spectral clustering

  • Author

    Siala, K. ; Benazza-Benyahia, A.

  • Author_Institution
    Departement de Mathematques Appliquees, Signal et Commun., Cite Technol. des Commun. de Tunis, Ariana, Tunisia
  • fYear
    2004
  • fDate
    2004
  • Firstpage
    435
  • Lastpage
    438
  • Abstract
    In this paper, we are interested in coding exactly and gradually hyperspectral image data. To this purpose, vector lifting schemes (VLS) are retained since they take into account the spatial and spectral redundancies in a multiresolution way. However, the high value of the number of components (some hundreds) prevents us applying directly the VLS, due to the tremendous operational complexity. Our contribution consists of a specific preprocessing of the hyperspectral images to make possible the use of VLS at the further stage. Experiments performed on AVIRIS images indicate the outperformance of the proposed method w.r.t. to the state-of-art coders.
  • Keywords
    geophysical signal processing; image coding; pattern clustering; remote sensing; vector quantisation; hyperspectral image compression; hyperspectral image data; image coding; spatial redundancies; spectral clustering; spectral redundancies; vector lifting schemes; Communications technology; High-resolution imaging; Hyperspectral imaging; Image coding; Image resolution; Monitoring; Optical imaging; Resource management; Spatial resolution; Spectroscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Communications and Signal Processing, 2004. First International Symposium on
  • Print_ISBN
    0-7803-8379-6
  • Type

    conf

  • DOI
    10.1109/ISCCSP.2004.1296322
  • Filename
    1296322