• DocumentCode
    2003812
  • Title

    Parametric morphological filters for pattern restoration

  • Author

    Schonfeld, Dan ; Goutsias, John

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
  • fYear
    1989
  • fDate
    6-8 Sep 1989
  • Firstpage
    188
  • Lastpage
    189
  • Abstract
    Summary form only given. A theoretical study of parametric morphological filters that best preserve the crucial topological structure of an input binary image from its noisy version is reported. The topological structure of the input binary image is given, and an arbitrary restoration filter is considered. A collection C of necessary and sufficient conditions for this filter to guarantee the restoration of a binary image from its noisy version, such that the input and restored images have identical topological structure, is derived. It is proved that each of the constraints in C generates a morphological filter. The approach used is to obtain a parametric filter that simultaneously satisfies as many of the constraints in C as possible
  • Keywords
    filtering and prediction theory; pattern recognition; picture processing; input binary image; noisy version; parametric morphological filters; pattern restoration; restoration filter; topological structure; Acoustics; Filtering theory; Filters; Geometry; Image analysis; Image processing; Image restoration; Laboratories; Morphology; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multidimensional Signal Processing Workshop, 1989., Sixth
  • Conference_Location
    Pacific Grove, CA
  • Type

    conf

  • DOI
    10.1109/MDSP.1989.97110
  • Filename
    97110