• DocumentCode
    1469455
  • Title

    Restoration and reconstruction from overlapping images for multi-image fusion

  • Author

    Reichenbach, Stephen E. ; Li, Jing

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Nebraska Univ., Lincoln, NE, USA
  • Volume
    39
  • Issue
    4
  • fYear
    2001
  • fDate
    4/1/2001 12:00:00 AM
  • Firstpage
    769
  • Lastpage
    780
  • Abstract
    This paper describes a technique for restoring and reconstructing a scene from overlapping images. In situations where there are multiple, overlapping images of the same scene, it may be desirable to create a single image that most closely approximates the scene, based on the data in all of the available images. For example, successive swaths acquired by NASA´s moderate imaging spectrometer (MODIS) will overlap, particularly at wide scan angles, creating a severe visual artifact in the output image. Resampling the overlapping swaths to produce a more accurate image on a uniform grid requires restoration and reconstruction. The one-pass restoration and reconstruction technique developed in this paper yields mean-square optimal resampling, based on a comprehensive end-to-end system model that accounts for image overlap and is subject to user-defined and data-availability constraints on the spatial support of the filter
  • Keywords
    geophysical signal processing; geophysical techniques; image reconstruction; image restoration; remote sensing; sensor fusion; terrain mapping; comprehensive end to end system model; filter; geophysical measurement technique; image fusion; image processing; image reconstruction; image restoration; land surface; mean square optimal resampling; multi-image fusion; one pass restoration; overlap; overlapping images; overlapping swath; remote sensing; resampling; sensor fusion; terrain mapping; Degradation; Digital images; Filters; Image reconstruction; Image restoration; Layout; MODIS; Optical imaging; Spectroscopy; Statistics;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.917891
  • Filename
    917891