• DocumentCode
    1242534
  • Title

    System considerations for multispectral image compression designs

  • Author

    Vaughn, Val D. ; Wilkinson, T.S.

  • Author_Institution
    Aerosp. Corp., El Segundo, CA, USA
  • Volume
    12
  • Issue
    1
  • fYear
    1995
  • fDate
    1/1/1995 12:00:00 AM
  • Firstpage
    19
  • Lastpage
    31
  • Abstract
    Multispectral image (MSI) compression has evolved into a viable solution for band limited communications problems in current and future remote sensing systems. MSI compression technology continues to mature as research identifies the interaction of compression distortion and typical multispectral exploitation tasks. Understanding of both compression artifacts and exploitation techniques must proceed in parallel because sensitivity to errors (distortion) must be addressed for a much larger usage base. This article provides an introduction to the experience gained from the Advanced Land Remote Sensing System (ALRSS) compression development, and an insight into the challenges of MSI and space-based compression algorithm design. The ALRSS studies provide an initial look at the challenges of designing and evaluating MSI compression systems. The results of these studies have shown that compression rates between 2.2 and 1.3 bpp are viable and feasible for space-based applications today. MSI systems can be designed to include compression without changing the significance of the final image product
  • Keywords
    data compression; image coding; remote sensing; spectral analysis; ALRSS; Advanced Land Remote Sensing System; band limited communications; compression artifacts; compression distortion; compression rates; multispectral exploitation tasks; multispectral image compression; remote sensing systems; space-based applications; space-based compression algorithm design; Image coding; Image resolution; Monitoring; Multispectral imaging; NASA; Remote sensing; Resource management; Satellites; Spatial resolution; US Department of Defense;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/79.363507
  • Filename
    363507