• DocumentCode
    2638491
  • Title

    Remote sensing image compression based on orientation-adaptive wavelet

  • Author

    Li, Tao ; Wu, Wenbo

  • Author_Institution
    Northwestern Polytech. Univ., Xi´´an
  • fYear
    2008
  • fDate
    10-12 Dec. 2008
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    This paper addresses the problem of image compression in remote sensing applications. Compared with other still images, remote-sensing images are characterized with complex textures and weak local correlation. As a fact, RS images often contain richly directional attributes, which can be commonly approximated as linear edges on a local level. Most of current algorithms of image compression have not taken this into account. In order to further improve coding efficiency, an efficient remote sensing image coding algorithm based on orientation-adaptive wavelet (OAW) is proposed. Compared to conventional lifting schemes, the method proposed can be performed at the direction where the pixels have a strong correlation, rather than always at the horizontal or vertical orientation. In the experiment, the author selects three satellite images to test the performance of the algorithm. Experimental results illustrate that it provides higher performance than traditional lifting schemes in low-bits compression.
  • Keywords
    data compression; image coding; remote sensing; wavelet transforms; linear edges; orientation-adaptive wavelet; pixel correlation; remote sensing image coding algorithm; remote sensing image compression; satellite images; Acceleration; Aerodynamics; Atmosphere; Drag; Earth; Heating; Image coding; Remote sensing; Trajectory; Vehicle dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Control in Aerospace and Astronautics, 2008. ISSCAA 2008. 2nd International Symposium on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-3908-9
  • Electronic_ISBN
    978-1-4244-2386-6
  • Type

    conf

  • DOI
    10.1109/ISSCAA.2008.4776319
  • Filename
    4776319