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Proceedings Paper

Contribution of non-negative matrix factorization to the classification of remote sensing images
Author(s): M. S. Karoui; Y. Deville; S. Hosseini; A. Ouamri; D. Ducrot
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Paper Abstract

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. The classification process requires some pre-processing, especially for data size reduction. The most usual technique is Principal Component Analysis. Another approach consists in regarding each pixel of the multispectral image as a mixture of pure elements contained in the observed area. Using Blind Source Separation (BSS) methods, one can hope to unmix each pixel and to perform the recognition of the classes constituting the observed scene. Our contribution consists in using Non-negative Matrix Factorization (NMF) combined with sparse coding as a solution to BSS, in order to generate new images (which are at least partly separated images) using HRV SPOT images from Oran area (Algeria). These images are then used as inputs of a supervised classifier integrating textural information. The results of classifications of these "separated" images show a clear improvement (correct pixel classification rate improved by more than 20%) compared to classification of initial (i.e. non separated) images. These results show the contribution of NMF as an attractive pre-processing for classification of multispectral remote sensing imagery.

Paper Details

Date Published: 10 October 2008
PDF: 8 pages
Proc. SPIE 7109, Image and Signal Processing for Remote Sensing XIV, 71090X (10 October 2008); doi: 10.1117/12.799749
Show Author Affiliations
M. S. Karoui, Ctr. des Techniques Spatiales (Algeria)
Y. Deville, Lab. d'Astrophysique de Toulouse-Tarbes, Univ. de Toulouse, CNRS (France)
S. Hosseini, Lab. d'Astrophysique de Toulouse-Tarbes, Univ. de Toulouse, CNRS (France)
A. Ouamri, Univ. des Sciences et de la Technologie d'Oran (Algeria)
D. Ducrot, Ctr. d'Etudes Spatiales de la BIOsphere, Univ. de Toulouse, CNRS (France)

Published in SPIE Proceedings Vol. 7109:
Image and Signal Processing for Remote Sensing XIV
Lorenzo Bruzzone; Claudia Notarnicola; Francesco Posa, Editor(s)

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