Hyperspectral image segmentation: the butterfly approach

Nathalie Gorretta (1) , Gilles Rabatel (1) , Jean-Michel Roger (1) , Christophe Fiorio (2) , Camille Lelong (3)

1 UMR ITAP - Information – Technologies – Analyse Environnementale – Procédés Agricoles
2 ARITH - Arithmétique informatique
3 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale

Few methods are proposed in the litterature for coupling the spectral and the spatial dimension available on hyperspectral images. This paper proposes a generic segmentation scheme named butterfly based on an iterative process and a cross analysis of spectral and spatial information. Indeed, spatial and spatial structures are extracted in spatial and spectral space respectively both taking into account the other one. To apply this layout on hyperspectral imgages, we focus particulary on spatial and spectral structures i.e. topologic concepts and latent variable for the spatial and the spectral space respectively. Moreover, a cooperation scheme with these structures is proposed. Finally, results obtained on real hyperspectral images using this specific implementation of the butterfly approach are presented and discussed.

Mots clés: HYPERSPECTAL IMAGING; IMAGE SEGMENTATION; CHEMOMETRICS

Mots clés: IMAGERIE; SEGMENTATION D'IMAGE; CHIMIOMETRIE; IMAGERIE HYPERSPECTRALE

Domaines: Sciences de l'environnement

Nathalie Gorretta, Gilles Rabatel, Jean-Michel Roger, Christophe Fiorio, Camille Lelong. Hyperspectral image segmentation: the butterfly approach. 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Aug 2009, Grenoble, France. ⟨10.1109/WHISPERS.2009.5289062⟩. ⟨hal-00468859⟩