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Proceedings Paper

Linear spectral unmixing-based method including extended nonnegative matrix factorization for pan-sharpening multispectral remote sensing images
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Paper Abstract

This paper presents a new fusion approach for pan-sharpening multispectral remote sensing images. This approach, related to Linear Spectral Unmixing (LSU) techniques, includes Extended Nonnegative Matrix Factorization (ExNMF) for combining low spatial resolution multispectral and high spatial resolution panchromatic data. ExNMF is applied to different real multispectral and panchromatic data sets with different spatial resolutions and different number of spectral bands. The quality of pan-sharpened multispectral images is evaluated by the jointly spectral and spatial Quality with No Reference (QNR) index. Obtained results show that our proposed method outperforms the Principal Component Analysis (PCA) and Gram-Schmidt (GS)-based standard literature methods.

Paper Details

Date Published: 17 October 2013
PDF: 7 pages
Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 889205 (17 October 2013); doi: 10.1117/12.2028100
Show Author Affiliations
Moussa Sofiane Karoui, Ctr. National des Techniques Spatiales (Algeria)


Published in SPIE Proceedings Vol. 8892:
Image and Signal Processing for Remote Sensing XIX
Lorenzo Bruzzone, Editor(s)

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