Adaptive Image Filtering and Segmentation Using Robust Estimation of Intensity

  • Roman M. Palenichka
  • Peter Zinterhof
  • Iryna B. Ivasenko
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1876)

Abstract

A structure-adaptive approach to robust statistical estimation of image intensity for adaptive filtering and segmentation of images is described in the context of a two-region structural image model. The proposed adaptive estimation procedure is based on the selection of best fitting structuring region relatively to a current point from all available multiple structuring regions by the maximum a posteriori probability principle. In application to image filtering, the described method allows to suppress noise and, at the same time, not damage the initial image including corner edges and image fine details. It provides also a robust binary segmentation of local objects of interest and their edges on noisy background.

Keywords

Robust Estimation Impulsive Noise Polynomial Regression Model Binary Segmentation Robust Parameter Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Roman M. Palenichka
    • 1
  • Peter Zinterhof
    • 1
  • Iryna B. Ivasenko
    • 2
  1. 1.Salzburg UniversitySalzburgAustria
  2. 2.Inst. of Physics and MechanicsNational Academy of Sciences of UkraineLvivUkraine

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