Comparative study on morphological principal component analysis of hyperspectral images

Gianni Franchi (1) , Jesus Angulo (1)

1 CMM - Centre de Morphologie Mathématique

This paper deals with a problem of reducing the dimension of hyperspectral images using the principal component analysis. Since hyperspectral images are always reduced before any process, we choose to do this reduction by adding spatial information that can be useful then for classification process; to do it we choose to project our data in new spaces thanks mathematical morphology.

Mots clés: Index Terms— Statistical Learning; reduction of dimen-sion; Hyperspectral images; Morphology

Domaines: Traitement du signal et de l'image [eess.SP]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Machine Learning [stat.ML]

Gianni Franchi, Jesus Angulo. Comparative study on morphological principal component analysis of hyperspectral images. Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 6th Workshop on, Jun 2014, Lausanne, Switzerland. ⟨hal-01256947⟩