• DocumentCode
    10289
  • Title

    Automatic Detection of Orientation of Mapped Units via Directional Granulometric Analysis

  • Author

    Vardhan, S. Ashok ; Sagar, B. S. Daya ; Rajesh, Naga ; Rajashekara, H.M.

  • Author_Institution
    Wipro Technol., Bangalore, India
  • Volume
    10
  • Issue
    6
  • fYear
    2013
  • fDate
    Nov. 2013
  • Firstpage
    1449
  • Lastpage
    1453
  • Abstract
    Automatic detection of orientation of mapped units via directional granulometries is addressed in this letter. A flat symmetric structuring element (B) of size 3 × 3 with nine elements, which is a disk in eight-connectivity grid, is decomposed into four 1-D directional structuring elements (Bis). Multiscale opening transformations are performed on each mapped unit with respect to these four directional structuring elements to eventually compute direction-specific morphologic entropy values. Based on these values, the orientations of mapped units are classified into four classes that include those units with orientations of: i) South East-North West (B1), ii) North-South (B2), iii) South West-North East (B3), and iv) East-West (B4). We demonstrated this approach on five model objects, and nine major river basins extracted from DEM of Indian peninsular. This approach yields quantitative results, based on which the mapped units could be automatically classified into four different orientations.
  • Keywords
    digital elevation models; entropy; remote sensing; rivers; 1-D directional structuring elements; DEM; Indian peninsular; automatic orientation classification; automatic orientation detection; digital elevation models; direction-specific morphologic entropy value computation; directional granulometric analysis; eight-connectivity grid; flat symmetric structuring element; four directional structuring elements; major river basins; mapped unit orientations; model objects; multiscale opening transformations; orientation units; Directional granulometries; entropy; mathematical morphology; pattern spectrum; remote sensing; shape; water bodies;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2013.2260127
  • Filename
    6547647