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Deblurring and Sparse Unmixing for Hyperspectral Images
IEEE Transactions on Geoscience and Remote Sensing, 2013The main aim of this paper is to study total variation (TV) regularization in deblurring and sparse unmixing of hyperspectral images. In the model, we also incorporate blurring operators for dealing with blurring effects, particularly blurring operators for hyperspectral imaging whose point spread functions are generally system dependent and formed ...
Xi-Le Zhao +4 more
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A Dataset with Ground-Truth for Hyperspectral Unmixing
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018Spectral unmixing is one of the most important issues of hyperspectral data processing. However, the lack of publicly available dataset with ground-truth makes it difficult to evaluate and compare the performance of unmixing algorithms. In this work, we create several experimental scenes in our laboratory with controlled settings where the pure ...
Min Zhao 0014, Jie Chen 0022
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KMNET for Hyperspectral Unmixing
2023 IEEE India Geoscience and Remote Sensing Symposium (InGARSS), 2023Sankalp Dhondi +4 more
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Hyperspectral Unmixing with Simultaneous Dimensionality Estimation.
2012This paper is an elaboration of the simplex identification via split augmented Lagrangian (SISAL) algorithm (Bioucas-Dias, 2009) to blindly unmix hyperspectral data. SISAL is a linear hyperspectral unmixing method of the minimum volume class. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the ...
Nascimento, Jose, Bioucas-Dias, José M.
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Unbiased Validation of Hyperspectral Unmixing Algorithms
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023Lukasz Tulczyjew +4 more
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Spectral–Spatial-Weighted Multiview Collaborative Sparse Unmixing for Hyperspectral Images
IEEE Transactions on Geoscience and Remote Sensing, 2020Lin Qi, Xb Gao, Xinbo Gao
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Fast Orthogonal Projection for Hyperspectral Unmixing
IEEE Transactions on Geoscience and Remote Sensing, 2022Xuanwen Tao +6 more
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Endmember Variability in hyperspectral image unmixing
Variabilité spectrale dans le démélange d'images hyperspectrales La finesse de la résolution spectrale des images hyperspectrales en télédétection permet une analyse précise de la scène observée, mais leur résolution spatiale est limitée, et un pixel acquis par le capteur est souvent un mélange des contributions de différents matériaux.openaire +1 more source
Deep Ensembles for Hyperspectral Image Data Classification and Unmixing
Remote Sensing, 2021Michał Myller +2 more
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Total Variation Spatial Regularization for Sparse Hyperspectral Unmixing
IEEE Transactions on Geoscience and Remote Sensing, 2012J Bioucas-Dias +2 more
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