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Proceedings Paper

More results on AMM for endmember induction
Author(s): Manuel Grana; Josune Gallego
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Paper Abstract

We test a procedure for endmember extraction on a synthetic hyperspectral image. The procedure uses the Autoassociative Morphological Memories (AMM) as detectors of morphological independence conditions. To validate it we apply Convex Cone Analysis (CCA) to the same data. To generate the validation data, we synthesize the ground truth abundance images as the simulation of gaussian random fields and we use as ground truth endmembers some reflectance spectra obtained from the USGS repository.

Paper Details

Date Published: 5 February 2004
PDF: 12 pages
Proc. SPIE 5238, Image and Signal Processing for Remote Sensing IX, (5 February 2004); doi: 10.1117/12.510930
Show Author Affiliations
Manuel Grana, Univ. del Pais Vasco/Euskal Herriko Unib. (Spain)
Josune Gallego, Univ. del Pais Vasco/Euskal Herriko Unib. (Spain)


Published in SPIE Proceedings Vol. 5238:
Image and Signal Processing for Remote Sensing IX
Lorenzo Bruzzone, Editor(s)

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