• DocumentCode
    2456578
  • Title

    Generalized laplacians for man-made object detection in satellite images

  • Author

    Levy, Dor

  • Author_Institution
    Electr. Eng. Dept., Technion - Israel Inst. of Technol., Haifa, Israel
  • fYear
    2012
  • fDate
    14-17 Nov. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A discrete version of Bochner laplacian is used for man-made object detection in mostly-natural satellite images. This paper describes research made for studying in this context discrete versions of Bochner laplacian and Ricci curvature known from Riemannian geometry. These combinatorial operators act on cell-complexes instead of smooth manifolds - a concept originating in the work of Robin Forman, and adopts his more general concepts to images. The idea is that digital images are not the smooth manifolds we want them to be, but objects of discrete nature. Thus, referring an image as a cell-complex and using the appropriate operators is a more natural approach. This way there is no loss of information due to approximation made by the transition from the discrete to the continuous world. The discrete Bochner laplacian excels in other image processing tasks as well, such as sharpening and edge-detection, and can be used in diffusion processes.
  • Keywords
    approximation theory; geometry; image processing; image sensors; object detection; Ricci curvature; Riemannian geometry; Robin Forman; context discrete Bochner Laplacian version; diffusion process; edge-detection; image processing; information loss; man-made object detection; mostly-natural satellite imaging; smooth manifolds cell-complex; Diffusion processes; Geometry; Image edge detection; Laplace equations; Manifolds; Object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical & Electronics Engineers in Israel (IEEEI), 2012 IEEE 27th Convention of
  • Conference_Location
    Eilat
  • Print_ISBN
    978-1-4673-4682-5
  • Type

    conf

  • DOI
    10.1109/EEEI.2012.6377018
  • Filename
    6377018