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Fatima Zohra Benhalouche
PhD at USTO-MB
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Publications (4)
SPIE Journal Paper | 27 September 2022
Hyperspectral unmixing with a partial nonnegative matrix factorization-based method for a structured additively-tuned linear mixing model addressing spectral variability
JARS, Vol. 16, Issue 03, 030502, (September 2022) https://doi.org/10.1117/12.10.1117/1.JRS.16.030502
KEYWORDS: Data modeling, Matrices, Spectral models, Algorithm development, Associative arrays, Reconstruction algorithms, Error analysis, Standards development, Spatial resolution, Sensors
Proceedings Article | 7 October 2019 Paper
A pixel-by-pixel NMF-based method for hyperspectral unmixing using a new linear mixing model to address additively-tuned spectral variabilty
Salah Eddine Brezini, Moussa Sofiane Karoui, Fatima Zohra Benhalouche, Yannick Deville, Abdelaziz Ouamri
Proceedings Volume 11155, 111550I (2019) https://doi.org/10.1117/12.2533159
KEYWORDS: Remote sensing, Sensors, Hyperspectral imaging, Matrices, Spectral resolution, Spatial resolution
SPIE Journal Paper | 10 May 2017
Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization
Fatima Zohra Benhalouche, Moussa Sofiane Karoui, Yannick Deville, Abdelaziz Ouamri
JARS, Vol. 11, Issue 02, 025008, (May 2017) https://doi.org/10.1117/12.10.1117/1.JRS.11.025008
KEYWORDS: Image resolution, Data fusion, Hyperspectral imaging, Resolution enhancement technologies, Spatial resolution, Remote sensing, Multispectral imaging
Proceedings Article | 15 October 2015 Paper
Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data
Fatima Zohra Benhalouche , Moussa Sofiane Karoui, Yannick Deville, Abdelaziz Ouamri
Proceedings Volume 9643, 96430Y (2015) https://doi.org/10.1117/12.2194904
KEYWORDS: Data modeling, Spatial resolution, Hyperspectral imaging, LIDAR, Data integration, Multispectral imaging, Image fusion, Matrices, Signal processing, Remote sensing
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