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Proceedings Paper

Application of competitive neural networks for unsupervised analysis of hyperspectral remote sensing images
Author(s): Monica Tellechea; Manuel Grana Romay
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Paper Abstract

We study the application of Competitive Neural Networks (CNN) to the Unsupervised analysis of Remote Sensing Hyperspectral images. CNN are applied as clustering algorithms at the pixel level. We propose their use for the extraction of endmembers and evaluate them through the error induced by the compression/decompression with the CNN in the supervised classification of the images. We show results with the Self Organizing Map and Neural Gas applied to a well known case study.

Paper Details

Date Published: 19 January 2001
PDF: 8 pages
Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001); doi: 10.1117/12.413882
Show Author Affiliations
Monica Tellechea, Univ. del Pais Vasco/Gipuzkoa (Spain)
Manuel Grana Romay, Univ. del Pais Vasco/Gipuzkoa (Spain)


Published in SPIE Proceedings Vol. 4170:
Image and Signal Processing for Remote Sensing VI
Sebastiano Bruno Serpico, Editor(s)

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