Relevant bibliographies by topics / Hyperspectral imaging

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Hyperspectral imaging'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Hyperspectral imaging"

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V, Prathama, and Dr Thippeswamy G. "Food Safety Control Using Hyperspectral Imaging." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 796–806. http://dx.doi.org/10.31142/ijtsrd10983.

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Müller-Rowold, M., and R. Reulke. "HYPERSPECTRAL PANORAMIC IMAGING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1 (September 26, 2018): 323–28. http://dx.doi.org/10.5194/isprs-archives-xlii-1-323-2018.

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<p><strong>Abstract.</strong> 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 Bepi Colombo).</p><p>There are basically two options for a hyperspectral system: Snapshot systems and scanning systems. This paper investigates a scanning hyperspectral push-broom systems. In most sy
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Bhargava, Rohit, and Kianoush Falahkheirkhah. "Enhancing hyperspectral imaging." Nature Machine Intelligence 3, no. 4 (2021): 279–80. http://dx.doi.org/10.1038/s42256-021-00336-9.

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Pitruzzello, Giampaolo. "Broadband hyperspectral imaging." Nature Photonics 19, no. 1 (2025): 11. https://doi.org/10.1038/s41566-024-01597-7.

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Lu, Bing, Phuong D. Dao, Jiangui Liu, Yuhong He, and Jiali Shang. "Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture." Remote Sensing 12, no. 16 (2020): 2659. http://dx.doi.org/10.3390/rs12162659.

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Remote sensing is a useful tool for monitoring spatio-temporal variations of crop morphological and physiological status and supporting practices in precision farming. In comparison with multispectral imaging, hyperspectral imaging is a more advanced technique that is capable of acquiring a detailed spectral response of target features. Due to limited accessibility outside of the scientific community, hyperspectral images have not been widely used in precision agriculture. In recent years, different mini-sized and low-cost airborne hyperspectral sensors (e.g., Headwall Micro-Hyperspec, Cubert
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Rui Zhou, Rui Zhou, Manping Ye Manping Ye, and Huacai Chen Huacai Chen. "Apple bruise detect with hyperspectral imaging technique." Chinese Optics Letters 12, s1 (2014): S11101–311103. http://dx.doi.org/10.3788/col201412.s11101.

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Changsheng Liu, Changsheng Liu, Zhimin Han Zhimin Han, and Tianyu Xie Tianyu Xie. "Hyperspectral high-dynamic-range endoscopic mucosal imaging." Chinese Optics Letters 13, no. 7 (2015): 071701–71705. http://dx.doi.org/10.3788/col201513.071701.

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Li, Yang, Yucheng Wei, Jiankang Zhou, and Juncheng Jia. "Research on design and implementation of high precision imaging colorimeter system." Highlights in Science, Engineering and Technology 120 (December 25, 2024): 807–13. https://doi.org/10.54097/tkfj7e02.

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As an important parameter to characterize the apparent characteristics of objects, color plays an irreplaceable role in various fields. With the increasing demand for color quality, special color detection instruments are needed to measure color quickly and accurately. However, the current traditional color measuring instrument has some limitations, it is difficult to accurately measure the color of a certain part of the complex pattern, and it is very easy to miss the image information of the object surface.With the continuous development of machine vision technology and spectrum technology,
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Wang, Zhixin, Peng Xu, Bohan Liu, Yankun Cao, Zhi Liu, and Zhaojun Liu. "Hyperspectral imaging for underwater object detection." Sensor Review 41, no. 2 (2021): 176–91. http://dx.doi.org/10.1108/sr-07-2020-0165.

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Purpose This paper aims to demonstrate the principle and practical applications of hyperspectral object detection, carry out the problem we now face and the possible solution. Also some challenges in this field are discussed. Design/methodology/approach First, the paper summarized the current research status of the hyperspectral techniques. Then, the paper demonstrated the development of underwater hyperspectral techniques from three major aspects, which are UHI preprocess, unmixing and applications. Finally, the paper presents a conclusion of applications of hyperspectral imaging and future r
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Chang, Chein-I., Meiping Song, Junping Zhang, and Chao-Cheng Wu. "Editorial for Special Issue “Hyperspectral Imaging and Applications”." Remote Sensing 11, no. 17 (2019): 2012. http://dx.doi.org/10.3390/rs11172012.

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Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. The aim of this Special Issue “Hyperspectral Imaging and Applications” is to publish new ideas and technologies to facilitate the utility of hyperspectral imaging in data exploitation and to further explore its potential in different applications. This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories, Data Unmixing,
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Dissertations / Theses on the topic "Hyperspectral imaging"

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Porter, Michael Anthony. "Hyperspectral imaging using ultraviolet light /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Dec%5FPorter.pdf.

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Thesis (M.S. in Astronautical Engineering)--Naval Postgraduate School, December 2005.<br>Thesis Advisor(s): Richard C. Olsen, Christopher Brophy. Includes bibliographical references (p.55-56). Also available online.
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Sjunnebo, Joakim. "Hyperspectral imaging for gas detection." Thesis, KTH, Tillämpad fysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169623.

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Porter, Michael A. "Hyperspectral imaging using ultraviolet light." Thesis, Monterey, California. Naval Postgraduate School, 2005. http://hdl.handle.net/10945/1817.

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The LINEATE IMAGING NEAR ULTRAVIOLET SPECTROMETER (LINUS) instrument has been used to remotely detect and measure sulfur dioxide (SO2). The sensor was calibrated in the lab, with curves of growth created for the 0.29 0.31 æ - spectral range of the LINUS sensor. Field observations were made of a coal burning plant in St. Johnâ s, Arizona at a range of 537 m. The Salt River Coronado plant stacks were emitting on average about 100 ppm and 200 ppm from the left and right stacks respectively. Analysis of the LINUS data matched those values within a few percent. Possible uses for this technology i
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Jones, Julia Craven. "Infrared Hyperspectral Imaging Stokes Polarimeter." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145409.

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This work presents the design, development, and testing of a field portable imaging spectropolarimeter that operates over the short-wavelength and middle-wavelength portion of the infrared spectrum. The sensor includes a pair of sapphire Wollaston prisms and several high order retarders to produce the first infrared implementation of an imaging Fourier transform spectropolarimeter, providing for the measurement of the complete spectropolarimetric datacube over the passband. The Wollaston prisms serve as a birefringent interferometer with reduced sensitivity to vibration when compared to an une
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Hartke, John. "DUAL BAND HYPERSPECTRAL IMAGING SPECTROMETER." Diss., The University of Arizona, 2005. http://hdl.handle.net/10150/195994.

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A temporally and spatially non-scanning imaging spectrometer covering two separate spectral bands in the visible region using computed tomographic imaging techniques is described. The computed tomographic techniques allow for the construction of a three-dimensional hyperspectral data cube (x, y, &amp;#955;) from the two-dimensional input in a single frame time. A computer generated holographic dispersive grating is used to disperse the incoming light into several diffraction orders on a focal plane composed of interwoven pixels independently sensitive to the two bands of interest. Separatin
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MAKKI, IHAB. "Hyperspectral Imaging for Landmine Detection." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2700516.

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This PhD thesis aims at investigating the possibility to detect landmines using hyperspectral imaging. Using this technology, we are able to acquire at each pixel of the image spectral data in hundreds of wavelengths. So, at each pixel we obtain a reflectance spectrum that is used as fingerprint to identify the materials in each pixel, and mainly in our project help us to detect the presence of landmines. The proposed process works as follows: a preconfigured drone (hexarotor or octorotor) will carry the hyperspectral camera. This programmed drone is responsible of flying over the contam
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Nguyen, Dinh hoang. "Development of an optical system for preclinical molecular imaging of atherothrombosis." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCD062/document.

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Dans ce travail de thèse, nous développons des protocoles d'imagerie optique pour l'observation des nanoparticules sur des coupes de tissus afin de relier leur localisation et leur «comportement» à l'environnement biologique, en particulier son éventuel état pathologique. Nous avons synthétisé des agents de contraste bimodaux, sous forme de nanoparticules -NP- visibles en résonance magnétique et en optique, à base d'oxydes de fer et de zinc (Zn(Fe)O) avec une nouvelle méthode de polyol azéotropique dans des solvants glycoliques (DEG et PG). L'élimination de l'eau à l'aide de l'appareil Dean-St
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Frontera, Pons Joana Maria. "Robust target detection for Hyperspectral Imaging." Thesis, Supélec, 2014. http://www.theses.fr/2014SUPL0024/document.

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L'imagerie hyperspectrale (HSI) repose sur le fait que, pour un matériau donné, la quantité de rayonnement émis varie avec la longueur d'onde. Les capteurs HSI mesurent donc le rayonnement des matériaux au sein de chaque pixel pour un très grand nombre de bandes spectrales contiguës et fournissent des images contenant des informations à la fois spatiale et spectrale. Les méthodes classiques de détection adaptative supposent généralement que le fond est gaussien à vecteur moyenne nul ou connu. Cependant, quand le vecteur moyen est inconnu, comme c'est le cas pour l'image hyperspectrale, il doit
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Yijian, Meng. "Extreme Ultraviolet Hyperspectral Coherent Diffractive Imaging." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/31928.

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We demonstrate hyperspectral imaging using two time-delayed, coherent extreme ultraviolet (XUV) sources. The approach combines broadband XUV high-harmonic generation, holographic imaging, and Fourier transform spectroscopy. The two harmonics sources are spatially separated at generation,and overlap in the far field resulting in a double slit diffraction pattern. We record the two-dimensional intensity modulation as a function of relative time delay; the Fourier transform determines the spatially dependent spectrum. To reduce the delay jitter and improve the spectral resolution, we demonstrate
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Alabboud, Ied. "Human retinal oximetry using hyperspectral imaging." Thesis, Heriot-Watt University, 2009. http://hdl.handle.net/10399/2297.

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The aim of the work reported in this thesis was to investigate the possibility of measuring human retinal oxygen saturation using hyperspectral imaging. A direct non-invasive quantitative mapping of retinal oxygen saturation is enabled by hyperspectral imaging whereby the absorption spectra of oxygenated and deoxygenated haemoglobin are recorded and analysed. Implementation of spectral retinal imaging thus requires ophthalmic instrumentation capable of efficiently recording the requisite spectral data cube. For this purpose, a spectral retinal imager was developed for the first time by integra
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Books on the topic "Hyperspectral imaging"

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Chang, Chein-I. Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6.

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Aikio, Mauri. Hyperspectral prism-grating-prism imaging spectrograph. Technical Research Centre of Finland, 2001.

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Park, Bosoon, and Renfu Lu, eds. Hyperspectral Imaging Technology in Food and Agriculture. Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2836-1.

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Sun, Da-Wen. Hyperspectral imaging for food quality analysis and control. Academic, 2010.

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United States. National Aeronautics and Space Administration., ed. Planetary Hyperspectral Imager (PHI): PIDDP, final report. Hughes Danbury Optical Systems, 1996.

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Hans, Grahn, and Geladi Paul, eds. Techniques and applications of hyperspectral image analysis. J. Wiley, 2007.

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United States. National Aeronautics and Space Administration., ed. Programmable hyperspectral image mapper with on-array processing: [patent application]. National Aeronautics and Space Administration, 1992.

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United States. National Aeronautics and Space Administration., ed. Programmable hyperspectral image mapper with on-array processing: [patent application]. National Aeronautics and Space Administration, 1992.

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1963-, Arora M. K., ed. Advanced image processing techniques for remotely sensed hyperspectral data. Springer, 2004.

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Borengasser, Marcus. Hyperspectral remote sensing: Principles and applications. CRC Press, 2008.

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Book chapters on the topic "Hyperspectral imaging"

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Gowen, A. A., E. Gaston, and J. Burger. "Hyperspectral Imaging." In Food Engineering Series. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0311-5_9.

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Nieves, Juan Luis. "Hyperspectral Imaging." In Encyclopedia of Color Science and Technology. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-642-27851-8_425-1.

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Nieves, Juan Luis. "Hyperspectral Imaging." In Encyclopedia of Color Science and Technology. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-89862-5_425.

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Chang, Chein-I. "Introduction." In Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6_1.

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Chang, Chein-I. "Target Abundance-Constrained Mixed Pixel Classification (TACMPC)." In Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6_10.

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Chang, Chein-I. "Target Signature-Constrained Mixed Pixel Classification (TSCMPC): LCMV Classifiers." In Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6_11.

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Chang, Chein-I. "Target Signature-Constrained Mixed Pixel Classification (TSCMPC): Linearly Constrained Discriminant Analysis (LCDA)." In Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6_12.

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Chang, Chein-I. "Automatic Mixed Pixel Classification (AMPC): Unsupervised Mixed Pixel Classification." In Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6_13.

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Chang, Chein-I. "Automatic Mixed Pixel Classificatio (AMPC): Anomaly Classification." In Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6_14.

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Chang, Chein-I. "Automatic mixed pixel classification (AMPC): Linear spectral random mixture analysis (LSRMA)." In Hyperspectral Imaging. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9170-6_15.

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Conference papers on the topic "Hyperspectral imaging"

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Gloaguen, Richard, Aldino Rizaldy, Ahmed J. Afifi, et al. "Towards 3D Hyperspectral Imaging." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642828.

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Mahnkopf, Sven, Alexandre Fong, Sergey Etchin, David Demmer, and Thomas Haslett. "Hyperspectral imaging camera system." In Components and Packaging for Laser Systems XI, edited by Alexei L. Glebov, Ruth Houbertz, and Stefan W. Heinemann. SPIE, 2025. https://doi.org/10.1117/12.3043632.

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Placke, Marlon, Chiara Lindner, Felix Mann, et al. "Mid-IR hyperspectral imaging with undetected photons." In Quantum 2.0. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/quantum.2024.qtu4c.4.

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By combining a nonlinear interferometer in imaging-mode with Fourier-transform spectroscopy, we realize broadband mid-infrared hyperspectral acquisition with undetected photons. We demonstrate the novel imaging technique on polymer and bio-tissue samples using only near-infrared silicon-based cameras.
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Gutierrez-Navarro, Omar, Juan N. Mendoza-Chavarria, Rafael A. Casillas-Peñuelas, and Daniel U. Campos-Delgado. "Adulterated Honey Detection Based on Hyperspectral Imaging." In Latin America Optics and Photonics Conference. Optica Publishing Group, 2024. https://doi.org/10.1364/laop.2024.tu1c.3.

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We propose a method to detect adulterated honey relying on hyperspectral imaging. Our proposal uses linear unmixing and machine learning based on known honey spectra. The proposal was tested on a published database that achieved an accuracy of 0.92 to 0.99.
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Cui, Qi, and Liang Gao. "Compressive Hyperspectral Imaging." In Imaging Systems and Applications. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/isa.2023.im4e.6.

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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).
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Dai, Qionghai, Chenguang Ma, Jinli Suo, and Xun Cao. "Computational Hyperspectral Imaging." In JSAP-OSA Joint Symposia. OSA, 2014. http://dx.doi.org/10.1364/jsap.2014.20p_c4_5.

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Chang, Chein-I. "Progressive hyperspectral imaging." In SPIE Remote Sensing, edited by Bormin Huang and Antonio J. Plaza. SPIE, 2012. http://dx.doi.org/10.1117/12.979188.

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Nischan, Melissa L., Amy B. Newbury, Rose Joseph, et al. "Active hyperspectral imaging." In International Symposium on Optical Science and Technology. SPIE, 2000. http://dx.doi.org/10.1117/12.406578.

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Descour, M. R., C. E. Volin, B. K. Ford, E. L. Dereniak, P. D. Maker, and D. W. Wilson. "Snapshot Hyperspectral Imaging." In Integrated Computational Imaging Systems. OSA, 2001. http://dx.doi.org/10.1364/icis.2001.itha4.

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Descour, Michael, C. E. Volin, B. K. Ford, E. L. Dereniak, P. D. Maker, and D. W. Wilson. "Snapshot hyperspectral imaging." In Integrated Computational Imaging Systems. OSA, 2001. http://dx.doi.org/10.1364/icis.2001.iwb4.

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Reports on the topic "Hyperspectral imaging"

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Gittins, Christopher M., William J. Marinelli, and Anthony J. Ratkowski. Airis Hyperspectral Imaging Technology,. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada329070.

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Bissett, W. P. High Altitude Hyperspectral Imaging Spectroscopy. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada439987.

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Davis, Curtiss O. Hyperspectral Imaging of River Systems. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada572752.

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Davis, Curtiss O. Hyperspectral Imaging of River Systems. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada557150.

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Pokrzywinski, Kaytee, Cliff Morgan, Scott Bourne, Molly Reif, Kenneth Matheson, and Shea Hammond. A novel laboratory method for the detection and identification of cyanobacteria using hyperspectral imaging : hyperspectral imaging for cyanobacteria detection. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40966.

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To assist US Army Corps of Engineers resource managers in monitoring for cyanobacteria bloom events, a laboratory method using hyperspectral imaging has been developed. This method enables the rapid detection of cyanobacteria in large volumes and has the potential to be transitioned to aerial platforms for field deployment. Prior to field data collection, validation of the technology in the laboratory using monocultures was needed. This report describes the development of the detection method using hyperspectral imaging and the stability/reliability of these signatures for identification purpo
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Manolakis, D. Detection Algorithms for Hyperspectral Imaging Applications. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada399744.

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Thiyanarantnam, Pradeep, Stanley Osher, Susan Chen, Wotao Yin, and Kevin Kelly. Compressive Hyperspectral Imaging and Anomaly Detection. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada580327.

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Kwon, Heesung, Dalton Rosario, Neelam Gupta, et al. Hyperspectral Imaging and Obstacle Detection for Robotics Navigation. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada485820.

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Grimm, David C., David W. Messinger, John P. Kerekes, and John R. Schott. Hybridization of Hyperspectral Imaging Target Detection Algorithm Chains. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada431819.

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Wolf, Malima. Hyperspectral Imaging for the Identification of Light Metals. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1187882.

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