• DocumentCode
    1735728
  • Title

    A remote sensing image compression method suited to space-borne application

  • Author

    Yanxin, Yu ; Xue, Song

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Changchun Univ. of Sci. & Technol., Changchun, China
  • Volume
    2
  • fYear
    2011
  • Firstpage
    1132
  • Lastpage
    1135
  • Abstract
    With the development of space technology, the data of remote sensing image dramatically increase. In order to save storage space and channel bandwidth, remote sensing image must be compressed before transmitted from a spacecraft. However, the space conditions bring a lot of constraints on the image compression platform, such as much limited storage memory and the low complexity of the image compression algorithm. This paper presented an image compression method suited to the space-borne application. To solve the problem of large-size RS images taking up large cache, the compression scheme based on overlap blocks was taken. The overlap blocks of the image were multi-levelly decomposed by lifting wavelet. According to human visual characteristics, the lossless encoding method was used for the low-frequency sub-band most sensitive to human vision, and the bit-plane coding method was take for the remaining high-frequency sub-bands. Simulation results show that the algorithm can remove the blocking artifacts and realize the high quality image compression.
  • Keywords
    geophysical image processing; geophysical techniques; image coding; remote sensing; space vehicles; bit-plane coding method; channel bandwidth; high quality image compression; high-frequency subbands; human visual characteristics; image compression algorithm; image compression platform; large-size RS images; lossless encoding method; low-frequency subband; remote sensing image compression method; space conditions; space technology; space-borne application; spacecraft; storage memory; storage space; wavelet method; Algorithm design and analysis; Image coding; Image reconstruction; Remote sensing; Wavelet coefficients; adaptive threshold; image compression; remote sensing image; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2011 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4577-1586-0
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2011.6182160
  • Filename
    6182160