• DocumentCode
    3485300
  • Title

    Minimum spanning tree adaptive image filtering

  • Author

    Stawiaski, Jean ; Meyer, Fernand

  • Author_Institution
    CMM-Centre de morphologie Math., Math. et Syst., MINES Paristech, Fontainebleau, France
  • fYear
    2009
  • fDate
    7-10 Nov. 2009
  • Firstpage
    2245
  • Lastpage
    2248
  • Abstract
    The main focus of this paper is related to anisotropic morphological edge preserving filters. We present in this work neighborhood filters defined on the minimal spanning tree (MST) of an image (according to a local dissimilarity measure between adjacent pixels). The designed filters take advantage of the property of the MST to detect and follow the local features of an image. This approach leads to neighborhood filters where the structuring elements adapt their shape to the minimal spanning tree structure and therefore to the local image features. We demonstrate the quality of this method on natural and synthetic images.
  • Keywords
    adaptive filters; image processing; trees (mathematics); adaptive image filtering; anisotropic morphological edge preserving filters; local image features; minimal spanning tree structure; natural images; synthetic images; Adaptive filters; Anisotropic magnetoresistance; Computational efficiency; Filtering; Geophysics computing; Grid computing; Morphology; Pixel; Shape; Smoothing methods; Morphological filter; denoising; edge-preserving; minimal spanning tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2009 16th IEEE International Conference on
  • Conference_Location
    Cairo
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-5653-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2009.5413942
  • Filename
    5413942