• DocumentCode
    1494071
  • Title

    Precise Subpixel Disparity Measurement From Very Narrow Baseline Stereo

  • Author

    Morgan, Gareth Llewellyn Keith ; Liu, Jian Guo ; Yan, Hongshi

  • Author_Institution
    Dept. of Earth Sci. & Eng., Imperial Coll. London, London, UK
  • Volume
    48
  • Issue
    9
  • fYear
    2010
  • Firstpage
    3424
  • Lastpage
    3433
  • Abstract
    To obtain depth-from-stereo imagery, it is traditionally required that the baseline separation between images (or the base-to-height ratio) be very large in order to ensure the largest image disparity range for effective measurement. Typically, a B/H ratio in the range of 0.6-1 is preferred. As a consequence, most existing stereo-matching algorithms are designed to measure disparities reliably with only integer-pixel precision. However, wide baselines may increase the possibility of occlusion occurring between highly contrasting relief, imposing a serious problem to digital elevation model (DEM) generation in urban and highly dissected mountainous areas. A narrow-baseline stereo configuration can alleviate the problem significantly but requires very precise measurements of disparity at subpixel levels. In this paper, we demonstrate a stereo-matching algorithm, based upon the robust phase correlation method, that is capable of directly measuring disparities up to 1/50th pixel accuracy and precision. The algorithm enables complete and dense surface shape information to be retrieved from images with unconventionally low B/H ratios (e.g., less than 0.01), potentially allowing DEM generation from images that would otherwise not be deemed suitable for the purpose.
  • Keywords
    digital elevation models; geophysical image processing; geophysical techniques; stereo image processing; base-to-height ratio; digital elevation model; image disparity range; integer-pixel precision; narrow-baseline stereo configuration; precise subpixel disparity measurement; robust phase correlation method; stereo imagery; stereo-matching algorithms; Algorithm design and analysis; Cameras; Digital elevation models; Geometry; Pixel; Robustness; Satellites; Shape measurement; Stereo vision; Surface topography; Digital elevation model (DEM); phase correlation (PC); stereo vision; subpixel;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2010.2046672
  • Filename
    5466239