Structurally adaptive mathematical morphology on nonlinear scale-space representations

Abstract : Standard formulation of morphological operators is translation invariant in the space and in the intensity: the same processing is considered for each point of the image. A current challenging topic in mathematical morphology is the construction of adaptive operators. In previous works, the adaptive operators are based either on spatially variable neighbourhoods according to the local regularity, or on size variable neighbourhoods according to the local intensity. This paper introduces a new framework: the structurally adaptive mathematical morphology. More precisely, the rationale behind the present approach is to work on a nonlinear multi-scale image decomposition, and then to adapt intrinsically the size of the operator to the local scale of the structures. The properties of the derived operators are investigated and their practical performances are compared with respect to standard morphological operators using natural image examples.
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Communication dans un congrès
17th IEEE International Conference on Image Processing (ICIP), Sep 2010, Hong-Kong, Hong Kong SAR China. IEEE, pp.121-124, 2010, <10.1109/ICIP.2010.5651969>
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https://hal-mines-paristech.archives-ouvertes.fr/hal-00834432
Contributeur : Doriane Ibarra <>
Soumis le : samedi 15 juin 2013 - 08:41:20
Dernière modification le : mercredi 13 septembre 2017 - 01:03:02

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Jesus Angulo, Santiago Velasco-Forero. Structurally adaptive mathematical morphology on nonlinear scale-space representations. 17th IEEE International Conference on Image Processing (ICIP), Sep 2010, Hong-Kong, Hong Kong SAR China. IEEE, pp.121-124, 2010, <10.1109/ICIP.2010.5651969>. <hal-00834432>

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