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Survey of hyperspectral imaging and applications

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article deals with the survey of hyperspectral imaging and its applications. The article is devoted to a survey of the key areas in which hyperspatial imaging finds application. These areas include geological survey and mineralogy, plastic separation, food quality inspection, precision agriculture, landmine detection, medical imaging, and manufacturing processes. It can be stated that the possibilities where hyperspectral imaging can be used are numerous. Also, the application of such technology and its deployment needs a deep understanding of the problem to which we want to apply hyperspectral imaging. In general, it can be used where it is possible to compare images of the normal state against the current state with a comparison sample.
Rocznik
Strony
22--28
Opis fizyczny
Bibliogr. 27 poz., il. (w tym kolor.), 1 mapa
Twórcy
  • Slovak University of Technology, Faculty of Electrical Engineering and Information Technology, Institute of Robotics and Cybernetics, Slovakia
  • Slovak University of Technology, Faculty of Electrical Engineering and Information Technology, Institute of Robotics and Cybernetics, Slovakia
  • University of Žilina, The Faculty of Mechanical Engineering, Department of Industrial Engineering, Univerzitn´a 8215/1, 010 26 Žilina, Slovakia
  • St. Elizabeth Cancer Institute in Bratislava, Slovakia
Bibliografia
  • [1] Agriculture Trimble, What Is Precision Ag?, avaible online: http://https%3A%2F%2Fagriculture.trimble.com%2Fblog%2Fwhat-is-precision-ag%2F, cited (13.07.2022).
  • [2] Amigo J.M., Practical issues of hyperspectral imaging analysis of solid dosage forms, Analytical and Bioanalytical Chemistry, 398, 93-109, 2010.
  • [3] Amigo J.M., Babamoradi H., Elcoroaristizabal S., Hyperspectral image analysis. A tutorial, Analytica Chimica Acta, 896, 34-51, 2015.
  • [4] Bogfjellmo S., Hyperspectral Analysis of Plastic Particles in the Ocean, 2016.
  • [5] Bratchenko I. et al., In vivo hyperspectral imaging of skin malignant and benign tumors in visible spectrum, JBPE, 4, 010301, 2018.
  • [6] Earthobservatory. Precision Farming, avaible online: https://earthobservatory.nasa.gov/images/1139/precision-farming, cited (13.07.2022).
  • [7] Earthobservatory. Measuring Vegetation (NDVI & EVI), avaible online: https://earthobservatory.nasa.gov/features/MeasuringVegetation/measuring vegetation 2.php, cited (13.07.2022).
  • [8] Garrido-Novell C. et al., Grading and color evolution of apples using RGB and hyperspectral imaging vision cameras, Journal of Food Engineering, 113, 281-288, 2012.
  • [9] Gates D.M., Keegan H.J., Schleter J.C.,Weidner V.R., Spectral properties of plants, Applied Optics, 4, 11-20, 1965.
  • [10] GISGeography. Multispectral vs Hyperspectral Imagery Explained, avaible online: https://gisgeography.com/multispectral-vs-hyperspectral-imagery-explained/, cited (13.07.2022).
  • [11] Gniadecka, M. et al., Melanoma diagnosis by Raman spectroscopy and neural networks: Structure alterations in proteins and lipids in intact cancer tissue, Journal of Investigative Dermatology, 122, 443-449, 2004.
  • [12] Goetz A.F.H., Three decades of hyperspectral remote sensing of the Earth: A personal view, Remote Sensing of Environment, 113, S5-S16, 2009.
  • [13] Gowen A.A., O’Donnell C.P., Cullen P.J., Downey G., Frias J.M., Hyperspectral imaging - an emerging proces analytical tool for food quality and safety control, Trends in Food Science & Technology, 18, 590-598, 2007.
  • [14] Gruber F., Wollmann P., Schumm B., Grählert W., Kaskel S., Quality control of slot-die coated aluminium oxide layers for battery applications using hyperspectral imaging, Journal of Imaging, 2, 12, 2016.
  • [15] Hollstein F., Wohllebe M., Arnaiz S., Manjón D., Identification of bioplastics by NIR-SWIR-Hyperspectral-Imaging, Environmental Science, 1, 2015.
  • [16] IDL, An Introduction to Interactive Data Language, avaible online: https://people.ast.cam.ac.uk/˜vasily/idl/idl introduction.pdf, cited (13.07.2022).
  • [17] Jonáš D., Multispectral camera and its usage in robotics, Bachelor thesis, Bratislava, STU FEI, 82 p., 2017.
  • [18] Landminefree. Facts about landmines, avaible online: http://www.landminefree.org/2017/index.php/support/facts-about-landmines, cited (13.07.2022).
  • [19] Lu G., Fei B., Medical hyperspectral imaging: a review, Journal of Biomedical Optics, 19, 010901, 2014.
  • [20] Maathuis B., Remote sensing based detection of minefields, Geocarto International, 18, 51-60, 2003.
  • [21] Nikolakopoulos K.G. et al., Combined use of remote sensing data, mineralogical analyses, microstructure studies and geographic information system for geological mapping of antiparos island (Greece), Geosciences, 8, 96, 2018.
  • [22] Nishii T., Matsuzaki K., Morita S., Real-time determination and visualization of two independent quantities during a manufacturing process of pharmaceutical tablets by near-infrared hyperspectral imaging combined with multivariate analysis, International Journal of Pharmaceutics, 590, 119871, 2020.
  • [23] Rizk P., Al Saleh N., Younes R., Ilinca A., Khoder J., Hyperspectral imaging applied for the detection of wind turbine blade damage and icing, Remote Sensing Applications: Society and Environment, 18, 100291, 2020.
  • [24] Tan W. et al., The feasibility of early detection and grading of apple bruises using hyperspectral imaging: Early detection and grading of apple bruises, Journal of Chemometrics, 32, e3067, 2018.
  • [25] Tumeh P., Lerner J., Dicker D., El-Deiry W., Differentiation of vascular and non-vascular skin spectral signatures using in vivo hyperspectral radiometric imaging: Implications for monitoring angiogenesis, Cancer Biology & Therapy, 6, 447-453, 2007.
  • [26] Vejarano R., Siche R., Tesfaye W., Evaluation of biological contaminants in foods by hyperspectral imaging: A review, International Journal of Food Properties, 1-34, 2017.
  • [27] Ziph-Schatzberg L., Corning Specialty. Hyperspectral Imaging Enables Industrial Applications, avaible online: https://www.photonics.com/Articles/Hyperspectral_Imaging_Enables_Industrial/a56804, cited (13.07.2022).
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b8dbec9c-aa41-4a8c-a77e-17f17b96a9f6
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