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Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012 Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras.
J. Bioucas-Dias +6 more
semanticscholar +3 more sources
Nature Reviews Methods PrimersHyperspectral imaging (HSI) is an advanced sensing modality that simultaneously captures spatial and spectral information, enabling non-invasive, label-free analysis of material, chemical, and biological properties. This Primer presents a comprehensive overview of HSI, from the underlying physical principles and sensor architectures to key steps in ...
Danfeng Hong +8 more
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Hyperspectral Satellites, Evolution, and Development History
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral imaging has been emerged as a new generation of technology for earth observation and space exploration since the beginning of this millennium and widely used in various disciplinary and applications.
Shen-En Qian
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SpectralFormer: Rethinking Hyperspectral Image Classification With Transformers [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2021 Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepancies.
D. Hong +6 more
semanticscholar +1 more source
Unsupervised Domain Adaptation With Dense-Based Compaction for Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Enormously hard work of label obtaining leads to the lack of enough annotated samples in the hyperspectral imagery (HSI). The mentioned reality inferred the unsupervised classification performance barely satisfactorily.
Chunyan Yu +4 more
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A Spatial-Enhanced LSE-SFIM Algorithm for Hyperspectral and Multispectral Images Fusion
Remote Sensing, 2021 The fusion of a hyperspectral image (HSI) and multispectral image (MSI) can significantly improve the ability of ground target recognition and identification.
Yulei Wang +4 more
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A New Deep Convolutional Network for Effective Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral unmixing extracts pure spectral constituents (endmembers) and their corresponding abundance fractions from remotely sensed scenes. Most traditional hyperspectral unmixing methods require the results of other endmember extraction algorithms ...
Xuanwen Tao +7 more
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Graph Convolutional Networks for Hyperspectral Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2020 Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classification due to their ability to capture spatial–spectral feature representations.
D. Hong +5 more
semanticscholar +1 more source
Orthogonal Subspace Projection Target Detector for Hyperspectral Anomaly Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Orthogonal subspace projection (OSP) is a versatile hyperspectral imaging technique which has shown great potential in dimensionality reduction, target detection, spectral unmixing, etc. However, due to its inherent requirement of prior target knowledge,
Chein-I Chang, Hongju Cao, Meiping Song
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A broadband hyperspectral image sensor with high spatio-temporal resolution [PDF]
Nature, 2023 Hyperspectral imaging provides high-dimensional spatial–temporal–spectral information showing intrinsic matter characteristics1–5. Here we report an on-chip computational hyperspectral imaging framework with high spatial and temporal resolution.
Liheng Bian +11 more
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