Results 1 to 10 of about 76,982 (174)

Hyperspectral Imaging for Lateral Tumour Demarcation of High-risk Basal Cell Carcinomas during Mohs Micrographic Surgery [PDF]

open access: yesActa Dermato-Venereologica
Hyperspectral imaging is a non-invasive imaging modality showing potential in delineating tumour margins preoperatively. This pilot study evaluated the feasibility of using hyperspectral imaging to demarcate lateral margins of high-risk facial basal cell
Hannah Ceder   +4 more
doaj   +2 more sources

Hyperspectral Imaging

open access: yesVGC 2023 - Unveiling the dynamic Earth with digital methods : 5th Virtual Geoscience Conference ; Book of Abstracts, 2023
Hyperspectral imaging (HSI) technology is a combination of conventional imaging and spectroscopic techniques, which has a unique ability to simultaneously acquire both the spatial and spectral data of a specimen. The HSI is a novel optical tool in food processing that has a great potential for rapidly identifying bacteria (and possibly other ...
Lorenz, Sandra, Kirsch, Moritz
openaire   +4 more sources

Unsupervised Domain Adaptation With Dense-Based Compaction for Hyperspectral Imagery

open access: yesIEEE 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
doaj   +1 more source

A Spatial-Enhanced LSE-SFIM Algorithm for Hyperspectral and Multispectral Images Fusion

open access: yesRemote 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
doaj   +1 more source

Orthogonal Subspace Projection Target Detector for Hyperspectral Anomaly Detection

open access: yesIEEE 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
doaj   +1 more source

HYPERSPECTRAL PANORAMIC IMAGING [PDF]

open access: yesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
Abstract. Hyperspectral instruments are designed for the characterisation of planetary surfaces, oceans and the atmosphere. At the moment there are a number of aircraft systems and planned space missions. Examples for this are the hyperspectral missions for Earth remote sensing (EnMAP) and also for deep space and planetary missions (Mercury mission ...
Müller-Rowold, Malte, Reulke, Ralf
openaire   +3 more sources

SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022 [PDF]

open access: yesEarth System Science Data, 2022
The drawbacks of low-coverage rate in global land inevitably exist in satellite-based daily soil moisture products because of the satellite orbit covering scopes and the limitations of soil moisture retrieving models.
Q. Zhang   +4 more
doaj   +1 more source

Interference-Suppressed and Cluster-Optimized Hyperspectral Target Extraction Based on Density Peak Clustering

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Target extraction can provide a prior knowledge for spectral unmixing, unsupervised hyperspectral image classification, and unsupervised target detection tasks, which is of great practice.
Xiaodi Shang   +4 more
doaj   +1 more source

Robust linear unmixing with enhanced constraint of classification for hyperspectral remote sensing imagery

open access: yesIET 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
doaj   +1 more source

A Simplified 2D-3D CNN Architecture for Hyperspectral Image Classification Based on Spatial–Spectral Fusion

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Convolutional neural networks (CNN) have led to a successful breakthrough for hyperspectral image classification (HSIC). Due to the intrinsic spatial-spectral specificities of a hyperspectral cube, feature extraction with 3-D convolution operation is a ...
Chunyan Yu   +4 more
doaj   +1 more source

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