Results 181 to 190 of about 6,322 (191)

Double reweighted sparse regression for hyperspectral unmixing

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Spectral unmixing is an important technology in hyperspectral image applications. Recently, sparse regression is widely used in hyperspectral unmixing. This paper proposes a double reweighted sparse regression method for hyperspectral unmixing. The proposed method enhances the sparsity of abundance fraction in both spectral and spatial domains through ...
Rui Wang, Heng-Chao Li, Wenzhi Liao, Aleksandra Pizurica   +3 more
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Sparse unmixing based denoising for hyperspectral images

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Until recently, hyperspectral image denoising was considered as a prior step to applications such as classification, detection, or unmixing. However, unmixing has been recently shown to also provide denoising due to its inherent property of representing pixels in terms of pure material signatures and their abundances. It is possible to eliminate sensor-
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Total variation regulatization in sparse hyperspectral unmixing

2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011
Hyperspectral unmixing has recently been addressed as a sparse regression problem by using predefined spectral libraries instead of image-derived endmembers in the unmixing process. This new approach has attracted much attention, as it sidesteps well known obstacles met in endmember extraction, such as the stopping criteria for the extraction process ...
Marian-Daniel Iordache, Jose M. Bioucas-Dias, Antonio Plaza   +2 more
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Dual Spatial Weighted Sparse Hyperspectral Unmixing

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 2022
Yonggang Chen, Chengzhi Deng, Shaoquan Zhang, Fan Li, Ningyuan Zhang, Shengqian Wang   +5 more
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Complete dictionary online learning for sparse unmixing

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Sparse unmixing has been successfully applied to hyperspectral remote sensing imagery, based on an available standard spectral library. However, as the number of hyperspectral remote sensors increases, more and more hyperspectral remote sensing images are requiring analysis without the use of a corresponding standard spectral library.
Ruyi Feng, Yanfei Zhong, Liangpei Zhang
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Kernel sparse NMF for hyperspectral unmixing

2014 International Conference on Orange Technologies, 2014
Bei Fang, Ying Li, Peng Zhang, Bendu Bai
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Efficient Hyperspectral Sparse Regression Unmixing With Multilayers

IEEE Transactions on Geoscience and Remote Sensing, 2023
Xiangfei Shen, Lihui Chen, Haijun Liu, Xi Su, Wenjia Wei, Xia Zhu, Xichuan Zhou   +6 more
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Multiobjective Sparse Unmixing Based Hyperspectral Change Detection

Applied Soft Computing
Xiangming Jiang, Tianqi Gao, Maoguo Gong, Fenlong Jiang, Mingyang Zhang, Jieyi Liu   +5 more
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Multiobjective Coevolutionary Bayesian Learning for Hyperspectral Sparse Unmixing

Applied Soft Computing
Yiting Liu, Maoguo Gong, Xiangming Jiang, Jianzhao Li, Yue Zhao, Yan Pu, Ziqi Di   +6 more
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Sparse Coding Inspired GAN for Hyperspectral Unmixing

2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Soorya Suresh, Arun P V, Alok Porwal
openaire   +1 more source