MORPHOLOGICAL SEGMENTATION OF HYPERSPECTRAL IMAGES

Guillaume Noyel, Jesús Angulo, Dominique Jeulin

Abstract

The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted to the different hyperspectral functions. Data reduction is performed either by Factor Analysis or by model fitting. Image segmentation is done on different spaces: factor space, parameters space, etc. On all these spaces the spatial/spectral segmentation approach is applied, leading to relevant results on the image.

Keywords
factor analysis; hyperspectral imagery; mathematical morphology; watershed segmentation

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DOI: 10.5566/ias.v26.p101-109

Image Analysis & Stereology
EISSN 1854-5165 (Electronic version)
ISSN 1580-3139 (Printed version)