Application of pixel segmentation to the low rate compression of complex SAR imagery

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This paper describes a technique to identify pixels within a subregion (chip) of a complex or detected SAR image which are to be losslessly compressed while the remainder of the image is subjected to a high compression ratio. This multi-modal compression is required for the intelligent low rate compression of SAR imagery, which addresses the problem of transmitting massive amounts of high resolution complex SAR data from a remote airborne sensor to a ground station for exploitation by an automatic target recognition (ATR) system, in a real time environment, over a narrow bandwidth. The ATR system results might then be ... continued below

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6 p.

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Ives, R. W.; Eichel, P. & Magotra, N. March 1998.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

This paper describes a technique to identify pixels within a subregion (chip) of a complex or detected SAR image which are to be losslessly compressed while the remainder of the image is subjected to a high compression ratio. This multi-modal compression is required for the intelligent low rate compression of SAR imagery, which addresses the problem of transmitting massive amounts of high resolution complex SAR data from a remote airborne sensor to a ground station for exploitation by an automatic target recognition (ATR) system, in a real time environment, over a narrow bandwidth. The ATR system results might then be presented to an image analyst who, using the contextual information from the SAR image, makes final target determination.

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6 p.

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OSTI as DE98005029

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  • IEEE international geoscience and remote sensing symposium, Seattle, WA (United States), 6-10 Jul 1998

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  • Other: DE98005029
  • Report No.: SAND--98-0526C
  • Report No.: CONF-980715--
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 650366
  • Archival Resource Key: ark:/67531/metadc704761

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • March 1998

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  • Sept. 12, 2015, 6:31 a.m.

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  • May 5, 2016, 7:30 p.m.

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Ives, R. W.; Eichel, P. & Magotra, N. Application of pixel segmentation to the low rate compression of complex SAR imagery, article, March 1998; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc704761/: accessed December 13, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.