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Hyperspectral imaging: a new technique for aging blow fly pupae

, 2016
Sasha C. Voss, P.A. Magni, Christian Nansen, Ian R. Dadour   +3 more
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Spectral–Spatial Feature Tokenization Transformer for Hyperspectral Image Classification

IEEE Transactions on Geoscience and Remote Sensing, 2022
In hyperspectral image (HSI) classification, each pixel sample is assigned to a land-cover category. In the recent past, convolutional neural network (CNN)-based HSI classification methods have greatly improved performance due to their superior ability ...
Le Sun, Guangrui Zhao, Yuhui Zheng, Zebin Wu   +3 more
semanticscholar   +1 more source

Compressive Hyperspectral Imaging

Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP), 2023
Conventional hyperspectral cameras encounter a trade-off between spatial and spectral samplings while capturing an input scene. To address this problem, we propose two imaging systems: Hyperspectral Light Field Tomography (Hyper-LIFT) and Tunable Image Projection Spectrometry (TIPS).
Qi Cui, Liang Gao
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Hyperspectral Anomaly Detection: A survey

IEEE Geoscience and Remote Sensing Magazine, 2022
Hyperspectral imagery can obtain hundreds of narrow spectral bands of ground objects. The abundant and detailed spectral information offers a unique diagnostic identification ability for targets of interest.
H. Su, Zhaoyue Wu, Huihui Zhang, Q. Du
semanticscholar   +1 more source

Morphological Transformation and Spatial-Logical Aggregation for Tree Species Classification Using Hyperspectral Imagery

IEEE Transactions on Geoscience and Remote Sensing, 2023
Hyperspectral image (HSI) consists of abundant spectral and spatial characteristics, which contribute to a more accurate identification of materials and land covers.
Mengmeng Zhang, Wei Li, Xudong Zhao, Huan Liu, Ran Tao, Q. Du   +5 more
semanticscholar   +1 more source

Snapshot hyperspectral imaging

Integrated Computational Imaging Systems, 2001
Hyperspectral imaging associates a densely sampled spectral signature with each pixel in an imager’s field of view. The collected image data are in the form of a three-dimensional data set, i.e., an image cube. The image cube is also referred to as a hypercube or an object cube.
M.R. Descour, C.E. Volin, B.K. Ford, E.L. Dereniak, P.D. Maker, D.W. Wilson   +5 more
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Hyperspectral Image Transformer Classification Networks

IEEE Transactions on Geoscience and Remote Sensing, 2022
Hyperspectral image (HSI) classification is an important task in earth observation missions. Convolution neural networks (CNNs) with the powerful ability of feature extraction have shown prominence in HSI classification tasks. However, existing CNN-based
Xiaofei Yang, Weijia Cao, Yao Lu, Yicong Zhou   +3 more
semanticscholar   +1 more source

Hyperspectral confocal microscope

Applied Optics, 2006
We have developed a new, high performance, hyperspectral microscope for biological and other applications. For each voxel within a three-dimensional specimen, the microscope simultaneously records the emission spectrum from 500 nm to 800 nm, with better than 3 nm spectral resolution.
Michael B, Sinclair, David M, Haaland, Jerilyn A, Timlin, Howland D T, Jones   +3 more
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Hyperspectral Cytometry

2013
Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each ...
Gérald, Grégori, Bartek, Rajwa, Valery, Patsekin, James, Jones, Motohiro, Furuki, Masanobu, Yamamoto, J, Paul Robinson   +6 more
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