• DocumentCode
    1743194
  • Title

    Lossless compression of SAR imagery using a multiple-pass gradient adaptive lattice filter

  • Author

    Ives, Robert W.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., US Naval Postgraduate Sch., Monterey, CA, USA
  • Volume
    1
  • fYear
    2000
  • fDate
    Oct. 29 2000-Nov. 1 2000
  • Firstpage
    229
  • Abstract
    Synthetic aperture radar (SAR) is useful in many applications, including oil slick monitoring, terrain mapping and navigation, and automatic target recognition. Previous technological advances have resulted in data collections over larger areas at higher resolutions, generating massive amounts of data. Many effective compression techniques exist that can reduce the volume of data for storage and transmission with moderate loss of information. However, some SAR applications do not or cannot tolerate any compression loss (interferometry for example). This paper addresses a lossless SAR compression scheme that uses multiple passes of an adaptive filter to decorrelate the data prior to entropy coding.
  • Keywords
    adaptive filters; adaptive signal processing; data compression; decorrelation; entropy codes; filtering theory; image coding; lattice filters; radar imaging; radar target recognition; radionavigation; remote sensing by radar; synthetic aperture radar; terrain mapping; SAR applications; SAR imagery; automatic target recognition; data collection; data decorrelation; data storage; data transmission; entropy coding; interferometry; lossless compression; multiple-pass gradient adaptive lattice filter; navigation; oil slick monitoring; prediction compression algorithm; radar resolution; synthetic aperture radar; terrain mapping; Adaptive filters; Computerized monitoring; Image coding; Interferometry; Navigation; Petroleum; Propagation losses; Synthetic aperture radar; Target recognition; Terrain mapping;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA, USA
  • ISSN
    1058-6393
  • Print_ISBN
    0-7803-6514-3
  • Type

    conf

  • DOI
    10.1109/ACSSC.2000.910950
  • Filename
    910950