An edge-adapting Laplacian kernel for nonlinear diffusion filters

In this paper, first, a new Laplacian kernel is developed to integrate into it the anisotropic behavior to control the process of forward diffusion in horizontal and vertical directions. It is shown that, although the new kernel reduces the process of edge distortion, it nonetheless produces artifac...

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Détails bibliographiques
Publié dans:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 21(2012), 4 vom: 07. Apr., Seite 1561-72
Auteur principal: Hajiaboli, Mohammad Reza (Auteur)
Autres auteurs: Ahmad, M Omair, Wang, Chunyan
Format: Article en ligne
Langue:English
Publié: 2012
Accès à la collection:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Sujets:Journal Article Research Support, Non-U.S. Gov't
Description
Résumé:In this paper, first, a new Laplacian kernel is developed to integrate into it the anisotropic behavior to control the process of forward diffusion in horizontal and vertical directions. It is shown that, although the new kernel reduces the process of edge distortion, it nonetheless produces artifacts in the processed image. After examining the source of this problem, an analytical scheme is devised to obtain a spatially varying kernel that adapts itself to the diffusivity function. The proposed spatially varying Laplacian kernel is then used in various nonlinear diffusion filters starting from the classical Perona-Malik filter to the more recent ones. The effectiveness of the new kernel in terms of quantitative and qualitative measures is demonstrated by applying it to noisy images
Description:Date Completed 18.07.2012
Date Revised 22.03.2012
published: Print-Electronic
Citation Status MEDLINE
ISSN:1941-0042
DOI:10.1109/TIP.2011.2172803