• DocumentCode
    297871
  • Title

    A bounded distortion compression scheme for hyper-spectral image data

  • Author

    Memon, Nasir D.

  • Author_Institution
    Dept. of Comput. Sci., Northern Illinois Univ., DeKalb, IL, USA
  • Volume
    2
  • fYear
    1996
  • fDate
    27-31 May 1996
  • Firstpage
    1039
  • Abstract
    Presents a new approach for nearly lossless compression of multispectral image data that exploits both spectral and spatial correlations in a simple and adaptive manner. What the authors have described is just one choice of predictor, re-ordering and encoding. A number of alternatives can be used. Implementation results with a few different choices schemes are currently under investigation and will will be described at a later date. Also, the authors need to make more detailed comparisons of compression performances obtained with other lossy and nearly-lossless schemes given in the literature
  • Keywords
    adaptive signal processing; data compression; geophysical signal processing; geophysical techniques; image coding; linear predictive coding; remote sensing; sensor fusion; adaptive signal processing; bounded distortion compression scheme; encoding; geophysical measurement technique; hyperspectral image data compression; image processing; land surface; lossless compression; multispectral image data; nearly-lossless scheme; predictor; re-ordering; remote sensing; sensor fusion; signal processing; spatial correlation; spectral correlation; terrain mapping; Cause effect analysis; Computer science; Data compression; Entropy; Image analysis; Image coding; Image reconstruction; Performance analysis; Piecewise linear techniques; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International
  • Conference_Location
    Lincoln, NE
  • Print_ISBN
    0-7803-3068-4
  • Type

    conf

  • DOI
    10.1109/IGARSS.1996.516559
  • Filename
    516559