Results 1 to 10 of about 1,956 (163)
An Unmixing-Based Network for Underwater Target Detection From Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Detecting underwater targets from hyperspectral imagery makes a profound impact on marine exploration. Available methods mainly tackle this problem by modifying the land-based detection algorithms with classical bathymetric models, which usually fail to ...
Jiahao Qi +5 more
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A Non-Local Structure Tensor Based Approach for Multicomponent Image Recovery Problems
, 2014 Non-Local Total Variation (NLTV) has emerged as a useful tool in variational methods for image recovery problems. In this paper, we extend the NLTV-based regularization to multicomponent images by taking advantage of the Structure Tensor (ST) resulting ...
Chierchia, Giovanni +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 With the support of spectral libraries, sparse unmixing techniques have gradually developed. However, some existing sparse unmixing algorithms suffer from problems, such as insufficient utilization of spatial information and sensitivity to noise.
Yao Liang +4 more
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Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm [PDF]
, 2013 International audienceThis paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are post-nonlinear functions of unknown pure spectral components contaminated by an additive white
Altmann, Yoann +2 more
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Mamba-based spatial-spectral fusion network for hyperspectral unmixing
Journal of King Saud University: Computer and Information SciencesHyperspectral unmixing (HU) is a critical technique in hyperspectral image (HSI) analysis, aimed at decomposing mixed pixels into a set of spectral signatures (endmembers) and their corresponding abundance values.
Yuquan Gan, Jingtao Wei, Mengmeng Xu
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DSFC-AE: A New Hyperspectral Unmixing Method Based on Deep Shared Fully Connected Autoencoder
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe pervasive presence of mixed pixels in hyperspectral remote sensing imagery poses a substantial constraint on the quantitative progress of remote sensing technology. Hyperspectral unmixing (HU) techniques serve as effective means to address this issue.
Hao Chen +4 more
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Robust low-rank abundance matrix estimation for hyperspectral unmixing
The Journal of Engineering, 2019 Hyperspecral unmixing (HU) is one of the crucial steps of hyperspectral image (HSI) processing. The process of HU can be divided into end-member extraction and abundance estimation.
Fan Feng +4 more
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Unmixing-based gas plume tracking in LWIR hyperspectral video sequences
, 2016 International audienceIt is now possible to collect hyperspectral video sequences (HVS) at a near real-time frame rate. The wealth of spectral , spatial and temporal information of those sequences is particularly appealing for chemical gas plume tracking.
Chanussot, Jocelyn +3 more
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DNMF-AG: A Sparse Deep NMF Model with Adversarial Graph Regularization for Hyperspectral Unmixing
Remote SensingHyperspectral unmixing (HU) aims to extract constituent information from mixed pixels and is a fundamental task in hyperspectral remote sensing. Deep non-negative matrix factorization (DNMF) has recently attracted attention for HU due to its hierarchical
Kewen Qu, Xiaojuan Luo, Wenxing Bao
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Bilateral Filter Regularized L2 Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing
Remote Sensing, 2018 Hyperspectral unmixing (HU) is one of the most active hyperspectral image (HSI) processing research fields, which aims to identify the materials and their corresponding proportions in each HSI pixel. The extensions of the nonnegative matrix factorization
Zuoyu Zhang +4 more
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