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Journal articles on the topic 'High-resolution hyperspectral imaging'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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1

Zou, Chunbo, Jianfeng Yang, Dengshan Wu, et al. "Design and Test of Portable Hyperspectral Imaging Spectrometer." Journal of Sensors 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/7692491.

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We design and implement a portable hyperspectral imaging spectrometer, which has high spectral resolution, high spatial resolution, small volume, and low weight. The flight test has been conducted, and the hyperspectral images are acquired successfully. To achieve high performance, small volume, and regular appearance, an improved Dyson structure is designed and used in the hyperspectral imaging spectrometer. The hyperspectral imaging spectrometer is suitable for the small platform such as CubeSat and UAV (unmanned aerial vehicle), and it is also convenient to use for hyperspectral imaging acq
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Edwards, Paul R., Lethy Krishnan Jagadamma, Jochen Bruckbauer, et al. "High-Resolution Cathodoluminescence Hyperspectral Imaging of Nitride Nanostructures." Microscopy and Microanalysis 18, no. 6 (2012): 1212–19. http://dx.doi.org/10.1017/s1431927612013475.

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AbstractHyperspectral cathodoluminescence imaging provides spectrally and spatially resolved information on luminescent materials within a single dataset. Pushing the technique toward its ultimate nanoscale spatial limit, while at the same time spectrally dispersing the collected light before detection, increases the challenge of generating low-noise images. This article describes aspects of the instrumentation, and in particular data treatment methods, which address this problem. The methods are demonstrated by applying them to the analysis of nanoscale defect features and fabricated nanostru
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FAN, Xing-hao, Chun-yu LIU, Guang JIN, et al. "Small and high-resolution spaceborne hyperspectral imaging spectrometer." Optics and Precision Engineering 29, no. 3 (2021): 463–73. http://dx.doi.org/10.37188/ope.20212903.0463.

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4

Villegas, Arturo, and Juan P. Torres. "Spatial spectroscopy for high resolution imaging." EPJ Web of Conferences 238 (2020): 06005. http://dx.doi.org/10.1051/epjconf/202023806005.

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Quantum estimation theory provides bounds for the precision in the estimation of a set of parameters that characterize a system. Two questions naturally arise: Is any of these bounds tight? And if this is the case, what type of measurements can attain such a limit? In this work we show that for phase objects, it is possible to find a tight resolution bound. Moreover one can find a set of spatial modes whose detection provides an optimal estimation of the complete set of parameters for which we propose a homodyne detection scheme. We call this method spatial spectroscopy since it mimics in the
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Han, Xian-Hua, Yongqing Sun, Jian Wang, Boxin Shi, Yinqiang Zheng, and Yen-Wei Chen. "Spectral Representation via Data-Guided Sparsity for Hyperspectral Image Super-Resolution." Sensors 19, no. 24 (2019): 5401. http://dx.doi.org/10.3390/s19245401.

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Hyperspectral imaging is capable of acquiring the rich spectral information of scenes and has great potential for understanding the characteristics of different materials in many applications ranging from remote sensing to medical imaging. However, due to hardware limitations, the existed hyper-/multi-spectral imaging devices usually cannot obtain high spatial resolution. This study aims to generate a high resolution hyperspectral image according to the available low resolution hyperspectral and high resolution RGB images. We propose a novel hyperspectral image superresolution method via non-n
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Livens, S., K. Pauly, P. Baeck, et al. "A SPATIO-SPECTRAL CAMERA FOR HIGH RESOLUTION HYPERSPECTRAL IMAGING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 23, 2017): 223–28. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-223-2017.

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Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS) is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral i
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Jullien, Aurélie, Rémy Pascal, Umberto Bortolozzo, Nicolas Forget, and Stefania Residori. "High-resolution hyperspectral imaging with cascaded liquid crystal cells." Optica 4, no. 4 (2017): 400. http://dx.doi.org/10.1364/optica.4.000400.

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Seroul, Pierre, Mathieu Hébert, Marie Cherel, Romain Vernet, Raphael Clerc, and Matthieu Jomier. "Model-based Skin Pigment Cartography by High-Resolution Hyperspectral Imaging." Electronic Imaging 2017, no. 8 (2017): 108–14. http://dx.doi.org/10.2352/issn.2470-1173.2017.8.maap-281.

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Seroul, Pierre, Mathieu H�bert, Marie Cherel, Romain Vernet, Raphael Clerc, and Matthieu Jomier. "Model-based Skin Pigment Cartography by High-Resolution Hyperspectral Imaging." Journal of Imaging Science and Technology 60, no. 6 (2016): 604041–47. http://dx.doi.org/10.2352/j.imagingsci.technol.2016.60.6.060404.

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10

Zhang, Dong, Liyin Yuan, Shengwei Wang, et al. "Wide Swath and High Resolution Airborne HyperSpectral Imaging System and Flight Validation." Sensors 19, no. 7 (2019): 1667. http://dx.doi.org/10.3390/s19071667.

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Wide Swath and High Resolution Airborne Pushbroom Hyperspectral Imager (WiSHiRaPHI) is the new-generation airborne hyperspectral imager instrument of China, aimed at acquiring accurate spectral curve of target on the ground with both high spatial resolution and high spectral resolution. The spectral sampling interval of WiSHiRaPHI is 2.4 nm and the spectral resolution is 3.5 nm (FWHM), integrating 256 channels coving from 400 nm to 1000 nm. The instrument has a 40-degree field of view (FOV), 0.125 mrad instantaneous field of view (IFOV) and can work in high spectral resolution mode, high spati
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Juntunen, Cory, Isabel M. Woller, and Yongjin Sung. "Hyperspectral Three-Dimensional Fluorescence Imaging Using Snapshot Optical Tomography." Sensors 21, no. 11 (2021): 3652. http://dx.doi.org/10.3390/s21113652.

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Hyperspectral three-dimensional (3D) imaging can provide both 3D structural and functional information of a specimen. The imaging throughput is typically very low due to the requirement of scanning mechanisms for different depths and wavelengths. Here we demonstrate hyperspectral 3D imaging using Snapshot projection optical tomography (SPOT) and Fourier-transform spectroscopy (FTS). SPOT allows us to instantaneously acquire the projection images corresponding to different viewing angles, while FTS allows us to perform hyperspectral imaging at high spectral resolution. Using fluorescent beads a
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Marquez Castellanos, Miguel Angel, Cesar Augusto Vargas, and Henry Arguello. "Compact spatio-spectral algorithm for single image super-resolution in hyperspectral imaging." Ingeniería e Investigación 36, no. 3 (2016): 117. http://dx.doi.org/10.15446/ing.investig.v36n3.54267.

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Hyperspectral imaging (HSI) is used in a wide range of applications such as remote sensing, space imagery, mineral detection, and exploration. Unfortunately, it is difficult to acquire hyperspectral images with high spatial and spectral resolution due to instrument limitations. The super-resolution techniques are used to reconstruct low-resolution hyperspectral images. However, traditional superresolution (SR) approaches do not allow direct use of both spatial and spectral information, which is a decisive for an optimal reconstruction. This paper proposes a single image SR algorithm for HSI. T
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Devesse, Wim, Dieter De Baere, and Patrick Guillaume. "High Resolution Temperature Measurement of Liquid Stainless Steel Using Hyperspectral Imaging." Sensors 17, no. 1 (2017): 91. http://dx.doi.org/10.3390/s17010091.

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14

Dicker, David T., and Jeremy Lerner. "Differentiation of normal skin and melanoma using high resolution hyperspectral imaging." Cancer Biology & Therapy 5, no. 8 (2006): 1033–38. http://dx.doi.org/10.4161/cbt.5.8.3261.

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15

Jacq, Kévin, Charline Giguet-Covex, Pierre Sabatier, et al. "High-resolution grain size distribution of sediment core with hyperspectral imaging." Sedimentary Geology 393-394 (December 2019): 105536. http://dx.doi.org/10.1016/j.sedgeo.2019.105536.

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16

Magalhães, Filipe. "High-resolution hyperspectral single-pixel imaging system based on compressive sensing." Optical Engineering 51, no. 7 (2012): 071406. http://dx.doi.org/10.1117/1.oe.51.7.071406.

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17

Balsi, Marco, Monica Moroni, Valter Chiarabini, and Giovanni Tanda. "High-Resolution Aerial Detection of Marine Plastic Litter by Hyperspectral Sensing." Remote Sensing 13, no. 8 (2021): 1557. http://dx.doi.org/10.3390/rs13081557.

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An automatic custom-made procedure is developed to identify macroplastic debris loads in coastal and marine environment, through hyperspectral imaging from unmanned aerial vehicles (UAVs). Results obtained during a remote-sensing field campaign carried out in the seashore of Sassari (Sardinia, Italy) are presented. A push-broom-sensor-based spectral device, carried onboard a DJI Matrice 600 drone, was employed for the acquisition of spectral data in the range 900−1700 nm. The hyperspectral platform was realized by assembling commercial devices, whereas algorithms for mosaicking, post-flight ge
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18

Kashani, Amir H., Mark Wong, Nicole Koulisis, Chein-I. Chang, Gabriel Martin, and Mark S. Humayun. "Hyperspectral imaging of retinal microvascular anatomy." Journal of Biomedical Engineering and Informatics 2, no. 1 (2015): 139. http://dx.doi.org/10.5430/jbei.v2n1p139.

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Background: Hyperspectral image processing has been applied to many aspects of astronomical and earth science research. Furthermore, advances in computed tomographic imaging spectroscopy and diffraction grating design have allowed biological applications for non-invasive tissue analysis. Herein, we describe a hyperspectral computed tomographic imaging spectroscope (HCTIS) that provides high spatial, spectral and temporal resolution ideal for imaging biological tissue in vivo. Methods: We demonstrate proof-of-principle application of the HCTIS by imaging and mapping the microvascular anatomy of
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19

Delalieux, S., B. Delauré, L. Tits, M. Boonen, A. Sima, and P.-J. Baeck. "High resolution strawberry field monitoring using the compact hyperspectral imaging solution COSI." Advances in Animal Biosciences 8, no. 2 (2017): 156–61. http://dx.doi.org/10.1017/s2040470017001297.

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In strawberry production, a balanced and accurate irrigation schedule is essential, because of the high sensitivity of strawberry plants to water deficits and waterlogging. The optimal irrigation management strategy can, however, only be obtained by an accurate crop monitoring system. To replace the current visual inspection methods, which are subjective, time consuming and labour-intensive, the performance of the COmpact hyperSpectral Imaging system (COSI) mounted on an RPAS (Remotely Piloted Aircraft System) was evaluated. The study, focusing on different irrigation treatments in strawberry
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20

Nourrit, V., J. Denniss, M. M. K. Muqit, et al. "High-resolution hyperspectral imaging of the retina with a modified fundus camera." Journal Français d'Ophtalmologie 33, no. 10 (2010): 686–92. http://dx.doi.org/10.1016/j.jfo.2010.10.010.

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21

Gallay, Michal, Christoph Eck, Carlo Zgraggen, Ján Kaňuk, and Eduard Dvorný. "HIGH RESOLUTION AIRBORNE LASER SCANNING AND HYPERSPECTRAL IMAGING WITH A SMALL UAV PLATFORM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 823–27. http://dx.doi.org/10.5194/isprsarchives-xli-b1-823-2016.

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The capabilities of unmanned airborne systems (UAS) have become diverse with the recent development of lightweight remote sensing instruments. In this paper, we demonstrate our custom integration of the state-of-the-art technologies within an unmanned aerial platform capable of high-resolution and high-accuracy laser scanning, hyperspectral imaging, and photographic imaging. The technological solution comprises the latest development of a completely autonomous, unmanned helicopter by Aeroscout, the Scout B1-100 UAV helicopter. The helicopter is powered by a gasoline two-stroke engine and it al
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Gallay, Michal, Christoph Eck, Carlo Zgraggen, Ján Kaňuk, and Eduard Dvorný. "HIGH RESOLUTION AIRBORNE LASER SCANNING AND HYPERSPECTRAL IMAGING WITH A SMALL UAV PLATFORM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 823–27. http://dx.doi.org/10.5194/isprs-archives-xli-b1-823-2016.

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The capabilities of unmanned airborne systems (UAS) have become diverse with the recent development of lightweight remote sensing instruments. In this paper, we demonstrate our custom integration of the state-of-the-art technologies within an unmanned aerial platform capable of high-resolution and high-accuracy laser scanning, hyperspectral imaging, and photographic imaging. The technological solution comprises the latest development of a completely autonomous, unmanned helicopter by Aeroscout, the Scout B1-100 UAV helicopter. The helicopter is powered by a gasoline two-stroke engine and it al
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23

Kurz, T. H., and S. J. Buckley. "A REVIEW OF HYPERSPECTRAL IMAGING IN CLOSE RANGE APPLICATIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 16, 2016): 865–70. http://dx.doi.org/10.5194/isprsarchives-xli-b5-865-2016.

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Hyperspectral imaging is an established method for material mapping, which has been conventionally applied from airborne and spaceborne platforms for a range of applications, including mineral and vegetation mapping, change detection and environmental studies. The main advantage of lightweight hyperspectral imagers lies in the flexibility to deploy them from various platforms (terrestrial imaging and from unmanned aerial vehicles; UAVs), as well as the high spectral resolution to cover an expanding wavelength range. In addition, spatial resolution allows object sampling distances from micromet
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Kurz, T. H., and S. J. Buckley. "A REVIEW OF HYPERSPECTRAL IMAGING IN CLOSE RANGE APPLICATIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 16, 2016): 865–70. http://dx.doi.org/10.5194/isprs-archives-xli-b5-865-2016.

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Hyperspectral imaging is an established method for material mapping, which has been conventionally applied from airborne and spaceborne platforms for a range of applications, including mineral and vegetation mapping, change detection and environmental studies. The main advantage of lightweight hyperspectral imagers lies in the flexibility to deploy them from various platforms (terrestrial imaging and from unmanned aerial vehicles; UAVs), as well as the high spectral resolution to cover an expanding wavelength range. In addition, spatial resolution allows object sampling distances from micromet
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Ding, Na, Jiao Bo Gao, and Jun Wang. "Camouflage Target Identification Based on Hyperspectral Imaging System." Applied Mechanics and Materials 135-136 (October 2011): 341–46. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.341.

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A novel system of implementing target identification with hyperspectral imaging system based on acousto-optic tunable filter (AOTF) was proposed. The system consists of lens, AOTF, AOTF driver, CCD and image collection installation. Owing to the high spatial and spectral resolution, the system can operate in the spectral range from visible light to near infrared band. An experiment of detecting and recognizing of two different kinds of camouflage armets from background was presented. When the characteristic spectral wave bands are 680nm and 750nm, the two camouflage armets exhibit different sp
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Zhao, Jiangsan, Dmitry Kechasov, Boris Rewald, et al. "Deep Learning in Hyperspectral Image Reconstruction from Single RGB images—A Case Study on Tomato Quality Parameters." Remote Sensing 12, no. 19 (2020): 3258. http://dx.doi.org/10.3390/rs12193258.

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Hyperspectral imaging has many applications. However, the high device costs and low hyperspectral image resolution are major obstacles limiting its wider application in agriculture and other fields. Hyperspectral image reconstruction from a single RGB image fully addresses these two problems. The robust HSCNN-R model with mean relative absolute error loss function and evaluated by the Mean Relative Absolute Error metric was selected through permutation tests from models with combinations of loss functions and evaluation metrics, using tomato as a case study. Hyperspectral images were subsequen
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Sadeghi-Tehran, Pouria, Nicolas Virlet, and Malcolm J. Hawkesford. "A Neural Network Method for Classification of Sunlit and Shaded Components of Wheat Canopies in the Field Using High-Resolution Hyperspectral Imagery." Remote Sensing 13, no. 5 (2021): 898. http://dx.doi.org/10.3390/rs13050898.

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(1) Background: Information rich hyperspectral sensing, together with robust image analysis, is providing new research pathways in plant phenotyping. This combination facilitates the acquisition of spectral signatures of individual plant organs as well as providing detailed information about the physiological status of plants. Despite the advances in hyperspectral technology in field-based plant phenotyping, little is known about the characteristic spectral signatures of shaded and sunlit components in wheat canopies. Non-imaging hyperspectral sensors cannot provide spatial information; thus,
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Chen, Lulu, Yongqiang Zhao, Jiaxin Yao, et al. "Object Tracking in Hyperspectral-Oriented Video with Fast Spatial-Spectral Features." Remote Sensing 13, no. 10 (2021): 1922. http://dx.doi.org/10.3390/rs13101922.

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This paper presents a correlation filter object tracker based on fast spatial-spectral features (FSSF) to realize robust, real-time object tracking in hyperspectral surveillance video. Traditional object tracking in surveillance video based only on appearance information often fails in the presence of background clutter, low resolution, and appearance changes. Hyperspectral imaging uses unique spectral properties as well as spatial information to improve tracking accuracy in such challenging environments. However, the high-dimensionality of hyperspectral images causes high computational costs
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Devesse, Wim, Dieter De Baere, Michael Hinderdael, and Patrick Guillaume. "Model-Based Temperature Feedback Control of Laser Cladding Using High-Resolution Hyperspectral Imaging." IEEE/ASME Transactions on Mechatronics 22, no. 6 (2017): 2714–22. http://dx.doi.org/10.1109/tmech.2017.2754550.

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30

Davis, Robert E., Thomas H. Painter, Rick Forster, et al. "NASA Cold Land Processes Experiment (CLPX 2002/03): Spaceborne Remote Sensing." Journal of Hydrometeorology 9, no. 6 (2008): 1427–33. http://dx.doi.org/10.1175/2008jhm926.1.

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Abstract This paper describes satellite data collected as part of the 2002/03 Cold Land Processes Experiment (CLPX). These data include multispectral and hyperspectral optical imaging, and passive and active microwave observations of the test areas. The CLPX multispectral optical data include the Advanced Very High Resolution Radiometer (AVHRR), the Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Multi-angle Imaging Spectroradiometer (MISR). The spaceborne hyperspectral optical data consist of measurements acqu
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Contreras Acosta, Isabel Cecilia, Mahdi Khodadadzadeh, and Richard Gloaguen. "Resolution Enhancement for Drill-Core Hyperspectral Mineral Mapping." Remote Sensing 13, no. 12 (2021): 2296. http://dx.doi.org/10.3390/rs13122296.

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Drill-core samples are a key component in mineral exploration campaigns, and their rapid and objective analysis is becoming increasingly important. Hyperspectral imaging of drill-cores is a non-destructive technique that allows for non-invasive and fast mapping of mineral phases and alteration patterns. The use of adapted machine learning techniques such as supervised learning algorithms allows for a robust and accurate analysis of drill-core hyperspectral data. One of the remaining challenge is the spatial sampling of hyperspectral sensors in operational conditions, which does not allow us to
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Gruber, Florian, Philipp Wollmann, Wulf Grählert, and Stefan Kaskel. "Hyperspectral Imaging Using Laser Excitation for Fast Raman and Fluorescence Hyperspectral Imaging for Sorting and Quality Control Applications." Journal of Imaging 4, no. 10 (2018): 110. http://dx.doi.org/10.3390/jimaging4100110.

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A hyperspectral measurement system for the fast and large area measurement of Raman and fluorescence signals was developed, characterized and tested. This laser hyperspectral imaging system (Laser-HSI) can be used for sorting tasks and for continuous quality monitoring. The system uses a 532 nm Nd:YAG laser and a standard pushbroom HSI camera. Depending on the lens selected, it is possible to cover large areas (e.g., field of view (FOV) = 386 mm) or to achieve high spatial resolutions (e.g., 0.02 mm). The developed Laser-HSI was used for four exemplary experiments: (a) the measurement and clas
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Marwaha, R., A. Kumar, P. L. N. Raju, and Y. V. N. Krishna Murthy. "Target detection algorithm for airborne thermal hyperspectral data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 827–32. http://dx.doi.org/10.5194/isprsarchives-xl-8-827-2014.

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Airborne hyperspectral imaging is constantly being used for classification purpose. But airborne thermal hyperspectral image usually is a challenge for conventional classification approaches. The Telops Hyper-Cam sensor is an interferometer-based imaging system that helps in the spatial and spectral analysis of targets utilizing a single sensor. It is based on the technology of Fourier-transform which yields high spectral resolution and enables high accuracy radiometric calibration. The Hypercam instrument has 84 spectral bands in the 868 cm<sup>−1</sup> to 1280 cm<sup
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Carmona, E., J. Avbelj, K. Alonso, et al. "DATA PROCESSING FOR THE SPACE-BASED DESIS HYPERSPECTRAL SENSOR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 271–77. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-271-2017.

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The German Aerospace Center (DLR) and Teledyne Brown Engineering (TBE) have established a collaboration to develop and operate a new space-based hyperspectral sensor, the DLR Earth Sensing Imaging Spectrometer (DESIS). DESIS will provide spacebased hyperspectral data in the VNIR with high spectral resolution and near-global coverage. While TBE provides the platform and infrastructure for operation of the DESIS instrument on the International Space Station, DLR is responsible for providing the instrument and the processing software. The DESIS instrument is equipped with novel characteristics fo
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Aasen, Helge, and Andreas Bolten. "Multi-temporal high-resolution imaging spectroscopy with hyperspectral 2D imagers – From theory to application." Remote Sensing of Environment 205 (February 2018): 374–89. http://dx.doi.org/10.1016/j.rse.2017.10.043.

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Dumke, Ines, Stein M. Nornes, Autun Purser, et al. "First hyperspectral imaging survey of the deep seafloor: High-resolution mapping of manganese nodules." Remote Sensing of Environment 209 (May 2018): 19–30. http://dx.doi.org/10.1016/j.rse.2018.02.024.

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Jacq, Kévin, Yves Perrette, Bernard Fanget, et al. "High-resolution prediction of organic matter concentration with hyperspectral imaging on a sediment core." Science of The Total Environment 663 (May 2019): 236–44. http://dx.doi.org/10.1016/j.scitotenv.2019.01.320.

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Xie, E. Y., Z. Z. Chen, P. R. Edwards, et al. "Strain relaxation in InGaN/GaN micro-pillars evidenced by high resolution cathodoluminescence hyperspectral imaging." Journal of Applied Physics 112, no. 1 (2012): 013107. http://dx.doi.org/10.1063/1.4733335.

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Pani, Silvia, Sarene C. Saifuddin, Filipa I. M. Ferreira, et al. "High Energy Resolution Hyperspectral X-Ray Imaging for Low-Dose Contrast-Enhanced Digital Mammography." IEEE Transactions on Medical Imaging 36, no. 9 (2017): 1784–95. http://dx.doi.org/10.1109/tmi.2017.2706065.

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Tuşa, Laura, Mahdi Khodadadzadeh, Cecilia Contreras, et al. "Drill-Core Mineral Abundance Estimation Using Hyperspectral and High-Resolution Mineralogical Data." Remote Sensing 12, no. 7 (2020): 1218. http://dx.doi.org/10.3390/rs12071218.

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Due to the extensive drilling performed every year in exploration campaigns for the discovery and evaluation of ore deposits, drill-core mapping is becoming an essential step. While valuable mineralogical information is extracted during core logging by on-site geologists, the process is time consuming and dependent on the observer and individual background. Hyperspectral short-wave infrared (SWIR) data is used in the mining industry as a tool to complement traditional logging techniques and to provide a rapid and non-invasive analytical method for mineralogical characterization. Additionally,
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Liu, Bohan, Zhaojun Liu, Shaojie Men, et al. "Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review." Sensors 20, no. 17 (2020): 4962. http://dx.doi.org/10.3390/s20174962.

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Common methods of ocean remote sensing and seafloor surveying are mainly carried out by airborne and spaceborne hyperspectral imagers. However, the water column hinders the propagation of sunlight to deeper areas, thus limiting the scope of observation. As an emerging technology, underwater hyperspectral imaging (UHI) is an extension of hyperspectral imaging technology in air conditions, and is undergoing rapid development for applications in shallow and deep-sea environments. It is a close-range, high-resolution approach for detecting and mapping the seafloor. In this paper, we focus on the c
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Fu, Xianping, Xiaodi Shang, Xudong Sun, Haoyang Yu, Meiping Song, and Chein-I. Chang. "Underwater Hyperspectral Target Detection with Band Selection." Remote Sensing 12, no. 7 (2020): 1056. http://dx.doi.org/10.3390/rs12071056.

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Compared to multi-spectral imagery, hyperspectral imagery has very high spectral resolution with abundant spectral information. In underwater target detection, hyperspectral technology can be advantageous in the sense of a poor underwater imaging environment, complex background, or protective mechanism of aquatic organisms. Due to high data redundancy, slow imaging speed, and long processing of hyperspectral imagery, a direct use of hyperspectral images in detecting targets cannot meet the needs of rapid detection of underwater targets. To resolve this issue, a fast, hyperspectral underwater t
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Liu, L., L. Xu, and J. Peng. "3D RECONSTRUCTION FROM UAV-BASED HYPERSPECTRAL IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1073–77. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1073-2018.

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Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity
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44

Eon, Rehman S., Sarah Goldsmith, Charles M. Bachmann, et al. "Retrieval of Salt Marsh Above-Ground Biomass from High-Spatial Resolution Hyperspectral Imagery Using PROSAIL." Remote Sensing 11, no. 11 (2019): 1385. http://dx.doi.org/10.3390/rs11111385.

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Salt marsh vegetation density varies considerably on short spatial scales, complicating attempts to evaluate plant characteristics using airborne remote sensing approaches. In this study, we used a mast-mounted hyperspectral imaging system to obtain cm-scale imagery of a salt marsh chronosequence on Hog Island, VA, where the morphology and biomass of the dominant plant species, Spartina alterniflora, varies widely. The high-resolution hyperspectral imagery allowed the detailed delineation of variations in above-ground biomass, which we retrieved from the imagery using the PROSAIL radiative tra
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Mohammed Noori, Abbas, Sumaya Falih Hasan, Qayssar Mahmood Ajaj, Mustafa Ridha Mezaal, Helmi Z. M. Shafri, and Muntadher Aidi Shareef. "Fusion of Airborne Hyperspectral and WorldView2 Multispectral Images for Detailed Urban Land Cover Classification A case Study of Kuala Lumpur, Malaysia." International Journal of Engineering & Technology 7, no. 4.37 (2018): 202. http://dx.doi.org/10.14419/ijet.v7i4.37.24102.

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Detecting the features of urban areas in detail requires very high spatial and spectral resolution in images. Hyperspectral sensors usually offer high spectral resolution images with a low spatial resolution. By contrast, multispectral sensors produce high spatial resolution images with a poor spectral resolution. Therefore, numerous fusion algorithms and techniques have been proposed in recent years to obtain high-quality images with improved spatial and spectral resolutions by sensibly combining the data acquired for the same scene. This work aims to exploit the extracted information from im
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Bruckbauer, Jochen, Paul R. Edwards, Tao Wang, and Robert W. Martin. "High resolution cathodoluminescence hyperspectral imaging of surface features in InGaN/GaN multiple quantum well structures." Applied Physics Letters 98, no. 14 (2011): 141908. http://dx.doi.org/10.1063/1.3575573.

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Zhang, Xiaofa, Wenyao Liu, Haiping Tong, et al. "High-Resolution Hyperspectral Microscopic Imaging With Single Acousto-Optic Tunable Filter Based on Double Filtering." IEEE Access 8 (2020): 11570–76. http://dx.doi.org/10.1109/access.2019.2963369.

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You, Hojun, and Dongsu Kim. "Development of an Image Registration Technique for Fluvial Hyperspectral Imagery Using an Optical Flow Algorithm." Sensors 21, no. 7 (2021): 2407. http://dx.doi.org/10.3390/s21072407.

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Fluvial remote sensing has been used to monitor diverse riverine properties through processes such as river bathymetry and visual detection of suspended sediment, algal blooms, and bed materials more efficiently than laborious and expensive in-situ measurements. Red–green–blue (RGB) optical sensors have been widely used in traditional fluvial remote sensing. However, owing to their three confined bands, they rely on visual inspection for qualitative assessments and are limited to performing quantitative and accurate monitoring. Recent advances in hyperspectral imaging in the fluvial domain hav
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Badola, Anushree, Santosh K. Panda, Dar A. Roberts, et al. "Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska." Remote Sensing 13, no. 9 (2021): 1693. http://dx.doi.org/10.3390/rs13091693.

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Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral da
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Okada, Natsuo, Yohei Maekawa, Narihiro Owada, Kazutoshi Haga, Atsushi Shibayama, and Youhei Kawamura. "Automated Identification of Mineral Types and Grain Size Using Hyperspectral Imaging and Deep Learning for Mineral Processing." Minerals 10, no. 9 (2020): 809. http://dx.doi.org/10.3390/min10090809.

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In mining operations, an ore is separated into its constituents through mineral processing methods, such as flotation. Identifying the type of minerals contained in the ore in advance aids greatly in performing faster and more efficient mineral processing. The human eye can recognize visual information in three wavelength regions: red, green, and blue. With hyperspectral imaging, high resolution spectral data that contains information from the visible light wavelength region to the near infrared region can be obtained. Using deep learning, the features of the hyperspectral data can be extracte
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