Structure-adaptive filtering based on polynomial regression modeling of image intensity

Roman M. Palenichka; Peter Zinterhof

doi:10.1117/1.1350558

1 April 2001 Structure-adaptive filtering based on polynomial regression modeling of image intensity

Roman M. Palenichka, Peter Zinterhof

Journal of Electronic Imaging, Vol. 10, Issue 2, (April 2001). https://doi.org/10.1117/1.1350558

In this paper a structure-adaptive approach to the evaluation of image intensity for adaptive filtering is described in the context of mixed noise model: Gaussian noise and impulsive noise as outliers of the Gaussian distribution. The known adaptive filtering techniques often yield nonsatisfactory results in this case because the outliers are confused with image fine details such as corner edges and thin lines. The proposed adaptive estimation procedure is based on the selection of best fitting structuring region relatively to a current point from available multiple structuring regions by the maximum a posteriori probability principle. Robust estimation of image intensity in the current point is made by using the sample of pixels of the selected structuring region. The described method allows us to suppress mixed noise and at the same time not to damage the initial image including corner edges and other image fine details.

©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Roman M. Palenichka and Peter Zinterhof "Structure-adaptive filtering based on polynomial regression modeling of image intensity," Journal of Electronic Imaging 10(2), (1 April 2001). https://doi.org/10.1117/1.1350558

Published: 1 April 2001

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