Hyperspectral imaging in infrared region using compressed sensing methods

Title Alternative:Hyperspektrální zobrazování v infračervené oblasti využívající komprimované snímání
Simple item page
dc.contributor.authorHlubuček, Jiří
dc.contributor.authorŽídek, Karel
dc.date.accessioned2018-06-26
dc.date.accessioned2018-06-26
dc.date.available2018-06-30
dc.date.available2018-06-26
dc.date.issued2018
dc.description.abstractTento článek se zabývá hyperspektrálním zobrazováním v infračervené oblasti, simulacemi měření a rekonstrukcemi testovacích datakrychlí za použití metody komprimovaného snímání CASSI (Coded Aperture Snapshot Spectral Imaging). Provedli jsme simulace přítomnosti chemické látky na části obrazu a poté jsme zrekonstruovali její absorpční spektrum a lokalizovali ji z jediného snímku detektoru. Jinými slovy, ukázali jsme, že v podstatě je možné rekonstruovat řídkou 3D datakrychli z jediného 2D obrazu. Dále diskutujeme kvalitu rekonstruovaných dat a limity zvolených metod simulace.cs
dc.description.abstractDieser Artikel befasst sich mit dem hyperspektralen Abbilden im infraroten Bereich, mit Simulationen des Messens und mit Rekonstruktionen von Testdatenwürfeln unter Verwendung der Methode des komprimierten Scannens, genannt CASSI (Coded Aperture Snapshot Spectral Imaging). Wir haben Simulationen der Gegenwart eines chemischen Stoffes auf einem Teil des Bildes durchgeführt. Danach haben wir dessen Absorptionsspektrum rekonstruiert und es auf einer einzigen Aufnahme des Detektors lokalisiert. Mit anderen Worten haben wir gezeigt, dass es im Grunde möglich ist, den seltenen 3D-Datenwürfel auf einem einzigen 2D-Bild zu rekonstruieren. Weiter diskutieren wir die Qualität der rekonstruierten Daten und die Grenzen der gewählten Methoden der Simulation.de
dc.description.abstractWe provide a review of hyperspectral imaging in infrared region as well as simulation of measurements and reconstructions of test datacubes using the compressed sensing method CASSI (Coded Aperture Snapshot Spectral Imaging). We simulate the presence of the chemical compounds on parts of the image and then we reconstruct its absorption spectrum and localization back from a single snapshot. In other words, we prove that in principle it is possible to reconstruct a sparse 3D datactube from a single 2D dataset. Furthermore, we discuss the quality of the reconstructed data and limitations of the chosen simulation method.en
dc.description.abstractNiniejszy artykuł poświęcony jest obrazowaniu wielospektralnemu w zakresie podczerwieni, symulacjom pomiaru i odtwarzaniu testowych kostek danych przy wykorzystaniu metody compressed sensing CASSI (Coded Aperture Snapshot Spectral Imaging). Przeprowadziliśmy symulację obecności substancji chemicznej na części obrazu, po czym odtworzyliśmy jej widmo absorpcyjne i zlokalizowaliśmy ją z jednego obrazu zarejestrowanego przez czujnik. Innymi słowy, pokazaliśmy, że w zasadzie można odtworzyć niezbyt gęstą kostkę danych 3D z jednego tylko obrazu 2D. Ponadto omawiamy jakość odtworzonych danych oraz ograniczenia wybranych metod symulacyjnych.pl
dc.formattext
dc.format.extent24-32 s.
dc.identifier.doi10.15240/tul/004/2018-1-003
dc.identifier.eissn1803-9790
dc.identifier.issn1803-9782
dc.identifier.otherACC_2018_1_03
dc.identifier.urihttps://dspace.tul.cz/handle/15240/26401
dc.language.isoen
dc.licenseCC BY-NC 4.1
dc.publisherTechnická univerzita v Liberci, Česká republikacs
dc.relation.isbasedonARCE, G. R.; BRADY, D. J.; CARIN, L.; ARGUELLO, H.; KITTLE, D. S.: Compressive Coded Aperture Spectral Imaging: An Introduction. IEEE Signal Processing Magazine. 2014, 31(1), pp. 105–115. Available from WWW: https://ieeexplore.ieee.org/document/6678264/. DOI: 10.1109/MSP.2013.2278763
dc.relation.isbasedonBIOUCAS-DIAS, J. M.; FIGUEIREDO, M. A. T.: A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration. IEEE Transactions on Image Processing. 2007, 16(12), pp. 2992–3004. Available from WWW: https://ieeexplore.ieee.org/document/4358846/. DOI: 10.1109/TIP.2007.909319
dc.relation.isbasedonGENDRIN, C.; ROGGO, Y.; COLLET, C.: Pharmaceutical applications of vibrational chemical imaging and chemometrics: A review. Journal of Pharmaceutical and Biomedical Analysis. 2008, 48(3), pp. 533–553. DOI: 10.1016/j.jpba.2008.08.014
dc.relation.isbasedonSTUART, B. H.: Infrared Spectroscopy: Fundamentals and Applications. Wiley Press: London, UK, 2004, pp. 29–36. ISBN 978-0-470-85428-0.
dc.relation.isbasedonMANLEY, M.: Near-infrared spectroscopy and hyperspectral imaging: Non-destructive analysis of biological materials. Chemical Society Reviews. 2014, 43(24), pp. 8200–8214. DOI: 10.1039/C4CS00062E
dc.relation.isbasedonHUCK, Ch. W.; OZAKI, Y.; VERENA, A.; HUCK-PEZZEI, V. A.: Critical Review Upon the Role and Potential of Fluorescence and Near-Infrared Imaging and Absorption Spectroscopy in Cancer Related Cells, Serum, Saliva, Urine and Tissue Analysis. Current Medicinal Chemistry. 2016, 23(27), pp. 3052–3077. DOI: 10.2174/0929867323666160607110507
dc.relation.isbasedonTÜRKER-KAYA, S.; HUCK, Ch. W.: A Review of Mid-Infrared and Near-Infrared Imaging: Principles, Concepts and Applications in Plant Tissue Analysis. Molecules. 2017, 22(1), p. 168. DOI: 10.3390/molecules22010168
dc.relation.isbasedonJUNKERMANN, W.; BURGER, J. M.: A New Portable Instrument for Continuous Measurement of Formaldehyde in Ambient Air. Journal of Atmospheric and Oceanic Technology. 2006, 23(1), pp. 38–45. DOI: 10.1175/JTECH1831.1
dc.relation.isbasedonKATRAŠNIK, J.; BÜRMEN, M.; PERNUŠ, F.; LIKAR, B.: Spectral characterization and calibration of AOTF spectrometers and hyper-spectral imaging systems. Chemometrics and Intelligent Laboratory Systems. 2010, 101(1), pp. 23–29. DOI: 10.1016/j.chemolab.2009.11.012
dc.relation.isbasedonHAMMOND, S. V.; CLARKE, F. C.: The handbook of vibrational spectroscopy, sampling techniques, microscopy. In: Chalmers J. M.; Griffiths P. R. (eds), Wiley, Hoboken, 2002, pp. 1405–1431.
dc.relation.isbasedonCARRASCO, O.; GOMEZ, R. B.; CHAINANI, A.; ROPER, W. E.: Hyperspectral imaging applied to medical diagnoses and food safety. In: Proc. SPIE 5097, Geo-Spatial and Temporal Image and Data Exploitation III. (14 August 2003). DOI: 10.1117/12.502589
dc.relation.isbasedonMAHESH, S.; JAYAS, D. S.; PALIWAL, J.; WHITE, N. D. G.: Hyperspectral imaging to classify and monitor quality of agricultural materials. Journal of Stored Products Research. 2015, Vol. 61, pp. 17–26. DOI: 10.1016/j.jspr.2015.01.006
dc.relation.isbasedonFENG, Y.-Z.; SUN, D.-W.: Application of hyperspectral imaging in food safety inspection and control: a review. Critical Reviews in Food Science and Nutrition. 2012, 52(11), pp. 1039–1058. DOI: 10.1080/10408398.2011.651542
dc.relation.isbasedonSCHULER, R. L.; KISH, P. E.; PLESE, C. A.: Preliminary observations on the ability of hyperspectral imaging to provide detection and visualization of bloodstain patterns on black fabrics. Journal of Forensic Sciences. 2012, 57(6), 1562–1569. DOI: 10.1111/j.1556-4029.2012.02171.x
dc.relation.isbasedonEDELMAN, G. J.; GASTON, E.; van LEEUWEN, T. G.; CULLEN, P. J.; AALDERS, M. C. G.: Hyperspectral imaging for non-contact analysis of forensic traces. Forensic Science International. 2012, 223(1–3), pp. 28–39. DOI: 10.1016/j.forsciint.2012.09.012
dc.relation.isbasedonBALAS, C.; EPITROPOU, G.; TSAPRAS, A.; HADJINICOLAOU, N.: Hyperspectral imaging and spectral classification for pigment identification and mapping in paintings by El Greco and his workshop. Multimedia Tools and Applications. 2018, 77(8), pp. 9737–9751. DOI: 10.1007/s11042-017-5564-2
dc.relation.isbasedonGAO, L.; LIANG, J.; LI, Ch.; WANG, L. V.: Single-shot compressed ultrafast photography at one hundred billion frames per second. Nature. 2014, Vol. 516, pp. 74–77. DOI: 10.1038/nature14005
dc.relation.isbasedonFERNANDEZ, Ch. A.; GUENTHER, B. D.; GEHM, M. E.; BRADY, D. J.; SULLIVAN, M. E.: Longwave infrared (LWIR) coded aperture dispersive spectrometer. Frontiers in Optics. 2006, OSA Technical Digest (CD) (Optical Society of America, 2006), paper JSuA10. DOI: 10.1364/FIO.2006.JSuA10
dc.relation.isbasedonRUSSELL, T. A.; McMACKIN, L.; BRIDGE, B.; BARANIUK, R.: Compressive hyperspectral sensor for LWIR gas detection. Proc. SPIE 8365, Compressive Sensing. 2012, 83650C. DOI: 10.1117/12.919522
dc.relation.isbasedonDUPUIS, J. R.; KIRBY, M.; COSOFRET, B. R.: Longwave infrared compressive hyperspectral imager. Proc. SPIE 9482, Next-Generation Spectroscopic Technologies VIII. 2015, 94820Z. DOI: 10.1117/12.2177893
dc.relation.ispartofACC Journalen
dc.relation.isrefereedtrue
dc.subjecthyperspectral imagingen
dc.subjectinfrared spectrumen
dc.subjectspectroscopyen
dc.subjectcompressed sensingen
dc.titleHyperspectral imaging in infrared region using compressed sensing methodsen
dc.title.alternativeHyperspektrální zobrazování v infračervené oblasti využívající komprimované snímánícs
dc.title.alternativeHyperspektrales Abbilden im infraroten Bereich zur Anwendung komprimierten Scannensde
dc.title.alternativeObrazowanie wielospektralne w zakresie podczerwieni przy wykorzystaniu techniki compressed sensingpl
dc.typeArticleen
local.accessopen
local.citation.epage32
local.citation.spage24
local.fulltextyesen
local.relation.issue1
local.relation.volume24
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ACC_2018_1_03.pdf
Size:
628.61 KB
Format:
Adobe Portable Document Format
Description:
Článek
Download
Collections
2018/1 - Natural Sciences and Technology