Skip to Main content Skip to Navigation
Conference papers

An end-member based ordering relation for the morphological description of hyperspectral images

Erchan Aptoula 1 Nicolas Courty 2 Sébastien Lefèvre 2
2 OBELIX - Environment observation with complex imagery
UBS - Université de Bretagne Sud, IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : Despite the popularity of mathematical morphology with remote sensing image analysis, its application to hyperspectral data remains problematic. The issue stems from the need to impose a complete lattice structure on the multi-dimensional pixel value space, that requires a vector ordering. In this article , we introduce such a supervised ordering relation, which conversely to its alternatives, has been designed to be image-specific and exploits the spectral purity of pixels. The practical interest of the resulting multivariate morphological operators is validated through classification experiments where it achieves state-of-the-art performance.
Complete list of metadatas

Cited literature [15 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00998256
Contributor : Sébastien Lefèvre <>
Submitted on : Wednesday, November 13, 2019 - 5:39:16 PM
Last modification on : Thursday, April 2, 2020 - 1:55:04 AM

File

icip2014.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-00998256, version 1

Citation

Erchan Aptoula, Nicolas Courty, Sébastien Lefèvre. An end-member based ordering relation for the morphological description of hyperspectral images. IEEE International Conference on Image Processing (ICIP), Oct 2014, Paris, France. ⟨hal-00998256⟩

Share

Metrics

Record views

1049

Files downloads

88