Abstract : This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experiments on grayscale and color images demonstrate that these novel filters outperform classical morphological operations with a fixed, space-invariant structuring element for noise reduction applications. Tests on synthetic 3D images are then performed to show the high noise-reduction capacity of amoeba-based filters.
https://hal-mines-paristech.archives-ouvertes.fr/hal-01431825
Contributeur : Etienne Decencière
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Soumis le : mercredi 25 janvier 2017 - 09:18:05
Dernière modification le : mercredi 13 février 2019 - 14:24:02
Document(s) archivé(s) le : mercredi 26 avril 2017 - 12:36:47
