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SPATIAL STRUCTURES DETECTION IN HYPERSPECTRAL IMAGES USING MATHEMATICAL MORPHOLOGY
 

Summary: SPATIAL STRUCTURES DETECTION IN HYPERSPECTRAL IMAGES USING
MATHEMATICAL MORPHOLOGY
Santiago Velasco-Forero, Jesus Angulo
Mines ParisTech, Centre de Morphologie Math´ematique, Fontainebleau, France
ABSTRACT
The aim of this paper is to apply genuine hyperspectral math-
ematical morphology to extract spatial structures according
to their spectral nature. To achieve this objective, a novel ap-
proach for vectorial ordering is introduced in this paper. The
proposed ordering is based on a supervised framework which
requires a reference spectrum for the image background and,
at least, another reference spectrum for the image target. This
supervised ordering may then used for the extension of math-
ematical morphology to vectorial images and in particular, we
focus here on the application of morphological processing to
hyperspectral images, illustrating the performance with real
examples.
Index Terms-- Mathematical Morphology, Supervised
Learning, Spatial/Spectral Feature Extraction, Hyperspectral
Imagery.

  

Source: Angulo,Jesús - Centre de Morphologie Mathématique, Ecole des Mines de Paris

 

Collections: Computer Technologies and Information Sciences