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Article Dans Une Revue IEEE Journal of Selected Topics in Signal Processing Année : 2012

Random projection depth for multivariate mathematical morphology

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Jesus Angulo

Résumé

The open problem of the generalization of mathematical morphology to vector images is handled in this paper using the paradigm of depth functions. Statistical depth functions provide from the "deepest" point a "center-outward ordering" of a multidimensional data distribution and they can be therefore used to construct morphological operators. The fundamental assumption of this data-driven approach is the existence of "background/foreground" image representation. Examples in real color and hyperspectral images illustrate the results.
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Dates et versions

hal-00751347 , version 1 (13-11-2012)

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Santiago Velasco-Forero, Jesus Angulo. Random projection depth for multivariate mathematical morphology. IEEE Journal of Selected Topics in Signal Processing, 2012, 6 (7), pp.753-763. ⟨10.1109/JSTSP.2012.2211336⟩. ⟨hal-00751347⟩
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