Results 41 to 50 of about 1,407 (163)
IET Image Processing, 2022 Although hyperspectral data, especially spaceborne images, are rich in spectral information, their spatial resolution is usually low due to the limitation of sensor design and other factors.
Haoyang Yu +5 more
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Limnology and Oceanography: Methods, EarlyView.Abstract Cyanobacterial and other algal blooms are an environmental concern in waterbodies worldwide. While these blooms are a nuisance for recreational activities, they can also be harmful to human and wildlife health when the algae produce and release toxins.
Natalie C. Hall +7 more
wiley +1 more source
Raman Microspectroscopy for Structural Indication in Ultrafast Laser Writing
Small Methods, EarlyView.Raman microspectroscopy is demonstrated as an in situ, phase‐specific probe for femtosecond laser fabrication in diamond. Multiple spectral indicators are systematically evaluated and correlated with electrical performance, establishing a robust methodology for process monitoring.
Xingrui Cheng +5 more
wiley +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Sparse unmixing methods have been extensively studied as a popular topic in hyperspectral image analysis for several years. Fundamental model-based unmixing problems can be better reformulated by exploiting sparse constraints in different forms. Gradient-
Yapeng Miao, Bin Yang
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VIEW, EarlyView.In this work, we develop submicron‐resolution mapping of intracellular lipid elements (SMILE) as an extraction‐free vibrational spectroscopic imaging platform based on hyperspectral stimulated Raman scattering microscopy with a spectral analysis pipeline for pixel‐resolved lipid profiling.
Yihui Zhou +10 more
wiley +1 more source
Cluster-Wise Weighted NMF for Hyperspectral Images Unmixing with Imbalanced Data
Remote Sensing, 2021 Hyperspectral unmixing is an important technique for analyzing remote sensing images which aims to obtain a collection of endmembers and their corresponding abundances.
Xiaochen Lv, Wenhong Wang, Hongfu Liu
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Superpixel-Guided Matrix-Valued Kernel Functions for Multiscale Nonlinear Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral unmixing is a critical challenge in the analysis of hyperspectral remote sensing data. Due to the complex interactions between incident light and materials, which are significantly influenced by the three-dimensional geometry of the scene ...
Xiu Zhao, Meiping Song
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Rolling Guidance Based Scale-Aware Spatial Sparse Unmixing for Hyperspectral Remote Sensing Imagery
Remote Sensing, 2017 Spatial regularization based sparse unmixing has attracted much attention in the hyperspectral remote sensing image processing field, which combines spatial information consideration with a sparse unmixing model, and has achieved improved fractional ...
Ruyi Feng +3 more
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A Sparse Topic Relaxion and Group Clustering Model for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral unmixing (HU) has been a hot research topic in the field of hyperspectral remote sensing. In recent years, the employment of the probabilistic topic model to acquire the latent topics of hyperspectral images has been an effective method for
Qiqi Zhu +4 more
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Approximate Sparse Regularized Hyperspectral Unmixing [PDF]
Mathematical Problems in Engineering, 2014 Sparse regression based unmixing has been recently proposed to estimate the abundance of materials present in hyperspectral image pixel. In this paper, a novel sparse unmixing optimization model based on approximate sparsity, namely, approximate sparse unmixing (ASU), is firstly proposed to perform the unmixing task for hyperspectral remote sensing ...
Chengzhi Deng +6 more
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