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Morphological segmentation of hyperspectral images - ICSXII

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.
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Contributor : Guillaume Noyel Connect in order to contact the contributor
Submitted on : Tuesday, October 6, 2020 - 12:20:27 PM
Last modification on : Wednesday, November 17, 2021 - 12:27:18 PM
Long-term archiving on: : Thursday, January 7, 2021 - 6:24:26 PM

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  • HAL Id : hal-02958884, version 1

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Guillaume Noyel, Jesus Angulo, Dominique Jeulin. Morphological segmentation of hyperspectral images - ICSXII. 12th International Congress for Stereology (ICS XII), Université Jean Monnet, Aug 2007, Saint-Etienne, France. ⟨hal-02958884⟩

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