Hyperspectral Imaging Seminar


NOTE: Please send requests for lectures starting from 21:00 on Wednesday (1 May 2024). 

Emails arriving before 21:00 will not be considered.

Send at least 3 choices in order of preference. Shortlist of lectures can be found here.

Send requests by email to hagit@cs.haifa.ac.il

IMPORTANT: list the NUMBER + NAME of lecture (preferably pairs).

 

Course Homepage:
     http://cs.haifa.ac.il/hagit/courses/seminars/Hyperspectral/Hyperspectral.html
 
NO LESSONS:  22/5, 12/6, 26/6

 

General Reference:
See Intro Refs.


Lecture 1 – Introduction – What is Hyperspectral Imaging    (8/5/24a)     

·         Introduction to Hyperspectral Image Analysis
Peg Shippert, Ph.D., Earth Science Applications Specialist, Research Systems, Inc.
https://ohioopen.library.ohio.edu/cgi/viewcontent.cgi?article=1068&context=spacejournal

·         Intro to Hyperspectral Imaging
https://www.microimages.com/documentation/Tutorials/hyprspec.pdf

·         Multispectral vs Hyperspectral Imagery Explained
https://gisgeography.com/multispectral-vs-hyperspectral-imagery-explained/

 

Lecture 2 – Display of Hyperspectral Images on RGB Displays   (8/5/24b)      

Color Display for Hyperspectral Imagery
Qian Du, Shangshu Cai and Robert J. Moorhead,
IEEE Trans. On Geoscience and Remote Sensing, Vol 46(6), 2008
http://www.ece.msstate.edu/~du/TGRS-VIS2.pdf

·         A Low-Complexity Approach for Color Display of
Hyperspectral Remote-Sensing Images Using OneBit Transform Based Band Selection
Begüm Demir, Anıl Çelebi, and Sarp Ertürk
http://kulis.kocaeli.edu.tr/pub/tgrs08_hsidisplay.pdf
 

·         Design Goals and Solutions for Display of Hyperspectral Images
Nathaniel P. Jacobson, and Maya R. Gupta
IEEE Trans. On Geoscience and Remote Sensing, Vol 43(11), 2005
http://www.mayagupta.org/publications/JacobsonGuptaTGRS.pdf

·         Linear Fusion of Image Sets for Display
Nathaniel P. Jacobson, Maya R. Gupta and Jeffrey Cole
IEEE Trans. On Geoscience and Remote Sensing, Vol 45(10), 2007
http://www.umbc.edu/rssipl/people/jwang/citation_4.pdf
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4305369

 

·         Dimensionality Reduction for Useful Display of Hyperspectral Images
J. Cole
http://jeffcole.org/academics/image_display/image_display.pdf

 

Lecture 3 – Statistics of Hyperspectral Images    (Skip this lecture) 

·         Statistics of Real-World Hyperspectral Images
Ayan Chakrabarti and Todd Zickler
Harvard School of Engineering and Applied Sciences
http://vision.seas.harvard.edu/hyperspec/CZ_hss.pdf

·         Principal Component Analysis for Hyperspectral Image Classification.
Surveying and Land Information Science, Journal of the American Congress on Surveying and Mapping, No. 2, pp.115-122, 2002
Rodarmel, C., Shan, J.
https://engineering.purdue.edu/~jshan/publications/2002/SaLIS_2002_HyperImagesPCA.pdf

·         X On the Statistics of Hyperspectral Imaging Data
Dimitris Manolakis, David Marden, John Kerekes and Gary Shaw
MIT Lincoln Laboratory
https://ritdml.rit.edu/bitstream/handle/1850/3207/JKerekesConfProc04-16-2001.pdf?..


Lecture 4-5 – Classification and Target Identification in HI  (15/5/24a+15/5/24b) 

a) Whole Pixel (ssd/mse)

b) Angle distance

c) Spectral Feature Fitting

d) Sub-Pixel Methods

e) Complete Linear Spectral Unmixing

f) Matched Filtering (partial unmixing)

·         Review in:
Introduction to Hyperspectral Image Analysis
Peg Shippert, Ph.D., Earth Science Applications Specialist, Research Systems, Inc.
http://spacejournal.ohio.edu/pdf/shippert.pdf

·         Hyperspectral Image Processing for Automatic Target Detection Applications
Dimitris Manolakis, David Marden, and Gary A. Shaw
MIT Lincoln Laboratory
https://courses.cs.washington.edu/courses/cse591n/07sp/papers/14_1hyperspectralprocessing.pdf

·         A Bayesian Model and Gibbs Sampler for Hyperspectral Imaging.
Rodriguez-Yam, G., Davis, R.A., and Scharf, L.
Proceedings 2002 IEEE Sensor Array and Multichannel Signal Processing Workshop, Washington, D.C., 105-109, 2002
http://www.stat.columbia.edu/~rdavis/papers/rodriguezyam844.pdf

·         Unsupervised Unmixing of Hyperspectral Imagery Using the Constrained Positive Matrix Factorization
Yahya M. Masalmah
https://www.uprm.edu/cise/wp-content/uploads/sites/171/2018/12/masalmahcise.pdf

·         L1 Unmixing and its Application to Hyperspectral Image Enhancement
Zhaohui Guo, Todd Wittman and Stanley Osher
https://ww3.math.ucla.edu/camreport/cam09-30.pdf
(without the enhancing)

 

Lecture 6 - Hyperspectral Image Segmentation      (29/5/24a+29/5/24b)  
 

 

·         Morphological Segmentation of Hyperspectral Images
Guillaume Noyel, Jesus Angulo and Dominique Jeulin
Image Anal Stereol 2007;26:101-109
http://www.ias-iss.org/ojs/IAS/article/viewFile/813/716

·         Hyperspectral image segmentation and unmixing using hidden Markov trees
R Mittelman, AO Hero
Int Conf. Image Processing (ICIP), 2010
http://web.eecs.umich.edu/~hero/Preprints/mittelman_ICIP10.pdf

·         Hyperspectral image segmentation using binary partition trees
S Valero, P Salembier
Int Conf. Image Processing (ICIP), 2011
http://hal.archives-ouvertes.fr/docs/00/57/89/60/PDF/ieee_igarss_10_valero_new.pdf
http://perso.telecom-paristech.fr/~tupin/JTELE/PRES10/Valero.pdf

·         Metric Learning for Hyperspectral Image Segmentation
B. Bue, D. Thompson, M. Gilmore and R. Castaño,
Proc. IEEE WHISPERS 2011. Lisbon, PT., Jun. 2011.
http://www.ece.rice.edu/~bdb1/papers/whispers11_metric.pdf

·         Segmentation and Classification of Hyperspectral Images Using Minimum Spanning Forest Grown From Automatically Selected Markers
Yuliya Tarabalka, Jocelyn Chanussot, and Jón Atli Benediktsson
IEEE Transactions on System Man and Cybernetics, Vol 40(5),  2010
http://hal.inria.fr/docs/00/57/88/48/PDF/ieee_trans_10_tara_forest.pdf

·         Object segmentation in hyperspectral images using active contours and graph cutsSusi Huamán De La Vega &Vidya Manian
https://www.tandfonline.com/doi/abs/10.1080/01431161.2011.560208

 

Lecture 7 – Hyperspectral Image Denoising     (5/6/24a+5/6/24b) 

·         Noise Reduction in Hyperspectral Imagery: Overview and Application
Behnood Rasti, Paul Scheunders, Pedram Ghamisi, Giorgio Licciardi and Jocelyn Chanussot
Remote Sensing 2018, 10(3), 482
https://www.mdpi.com/2072-4292/10/3/482

·         Denoising of hyperspectral imagery using principal component analysis and wavelet shrinkage,
G. Chen and S.-E. Qian,
Geoscience and Remote Sensing, IEEE Transactions on, vol. 49, no. 3, pp. 973–980, 2011
https://pdfs.semanticscholar.org/e5d4/43601071344b466e94114b2d528d378c7c1e.pdf

·         Denoising Hyperspectral Imagery Using Principal Component Analysis and Block-Matching 4D Filtering
Chen, Guangyi; Bui, Tien D.; Quach, Kha Gia; Qian, Shen-En
Canadian Journal of Remote Sensing Volume 40, 2014 - Issue 1

·         Spectral Image Denoising with Cubic Total variation Model
H. Zhang
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume I-7, 2012
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-7/95/2012/isprsannals-I-7-95-2012.pdf

·         Wavelet Packets for multi- and hyper-spectral imagery
J. J. Benedetto, W. Czaja, M. Ehler, C. Flake, M. Hirn
https://www.researchgate.net/publication/252701859_Wavelet_Packets_for_multi-_and_hyper-spectral_imagery/link/0deec538487175ffc6000000/download?_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InB1YmxpY2F0aW9uIiwicGFnZSI6InB1YmxpY2F0aW9uIn19

·         Challenging:
Denoising Hyperspectral Imagery and Recovering Junk Bands using Wavelets and Sparse Approximation
Adam C. Zelinski and Vivek K Goyal
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4241251


Lecture 8 – HI Sensor Fusion           (Skip This year)

·         Prediction Accuracy of Color Imagery from Hyperspectral Imagery
Peter Bajcsy and Rob Kooper
https://isda.ncsa.illinois.edu/peter/publications/conferences/2005/PB-20050328-2.pdf

·         Multisensor Fusion with Hyperspectral Imaging Data: Detection and Classification
Su May Hsu , Hsiao-hua K. Burke
http://www.ll.mit.edu/publications/journal/pdf/vol14_no1/14_1multisensorfusion.pdf

·         Feature Based Fusion of Multisensor Data-Inclusion of Hyperspectral Data into Classification of High Resolution Orthophotos
A. Greiwe
http://www.ecognition.com/sites/default/files/290_ggrs2004_greiwe_g273.pdf

·         Too Simple:
Spectral Interpretation Based on Multisensor Fusion for Urban Mapping
Be΄ata Csath΄o, Toni Schenk and Suyoung Seo
http://rsl.geology.buffalo.edu/documents/csatho_berlin03_paper.pdf

·         Very Basic:
Comparative Image Fusion Analysais
Firooz Sadjadi
OTCBVS-05
http://www.cse.ohio-state.edu/OTCBVS/05/OTCBVS-05-FINALPAPERS/W01_13.pdf


Lecture 9 – HI Compression         (skip)  

·         Hyperspectral Image Compression Using Three-Dimensional Wavelet Coding
Xaoli Tang, William, A. Pearlman and James W. Modestino
http://www.cipr.rpi.edu/staff/pearlman.html/papers/tgars02_tp.pdf

·         Exploiting Calibration-Induced Artifacts in Lossless Compression of Hyperspectral Imagery
Aaron B. Kiely, and Matthew A. Klimesh
IEEE Trans. On Geoscience and Remote Sensing, Vol 46(6), 2008
http://compression.jpl.nasa.gov/hyperspectral/KielyKlimesh_HyperArtifacts_preprint.pdf


Lecture 10 – Face Recognition in Hyperspectral images      (19/6/24a) 
 

·         Face Recognition in Hyperspectral Images
Zhihong Pan,  Glenn Healey, Manish Prasad, and Bruce Tromberg
IEEE PAMI Vol 25 no 12 2003
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.210.4398&rep=rep1&type=pdf

·         Studies on Hyperspectral Face Recognition in Visible Spectrum with Feature Band Selection,  (Uses PCA)
Wei Di, Lei Zhang, David Zhang, and Quan Pan,
IEEE Transactions on Systems, Man, and Cybernetics — Part a: Systems and Humans,
Volume 40, No.6, 1354-1361, 2010.

·         Hyper spectral face image based biometric recognition  (also PCA)
Siddharth B. Dabhade ; Nagsen S. Bansod ; Yogesh S. Rode ; M. M. Kazi ; K
Int Conf on Global Trends in Signal Processing, Information Computing and
Communication (ICGTSPICC), 2016

·         Illumination Invariant Face Recognition Using Near-Infrared Images  (Uses LBP)
Stan Z. Li, RuFeng Chu, ShengCai Liao, and Lun Zhang
IEEE PAMI Vol 29 no 4, 627– 639,  2007
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.137.7331&rep=rep1&type=pdf

·         Towards Hyperspectral Face Recognition,   (fusion of Visible and NIR EMS)
Stefan A. Robila,
Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, Volume 6812, 2008

·         Pixel Based Supervised Classification of Hyperspectral Face Images for Face Recognition
Shwetanka Neeraja Jitendraa Vikeshb Kamal Jain
Procedia Computer Science Volume 132, Pages 706-717, 2018
https://www.sciencedirect.com/science/article/pii/S1877050918308093

 

Lecture 11 – Hyperspectral image analysis of skin   (Skip this lecture) 
   

Zonios Papers:

·         Skin Melanin, Hemoglobin, and Light Scattering Properties can be Quantitatively Assessed In Vivo Using Diffuse Reflectance Spectroscopy
George Zonios, Julie Bykowski, and Nikiforos Kollias
2001
http://www.science.mcmaster.ca/medphys/images/files/graduate/JournalClub/2011-2012/zonios2001.pdf

·         Light scattering spectroscopy of human skin in vivo
George Zonios and Aikaterini Dimou
1999
Only to page 6.
http://www.opticsinfobase.org/vjbo/fulltext.cfm?uri=oe-17-3-1256&id=176052
http://www.opticsinfobase.org/view_article.cfm?gotourl=http%3A%2F%2Fwww%2Eopticsinfobase%2Eorg%2FDirectPDFAccess%2F5220FD0C-AFE7-9FDB-9EB32CB88D71D2D5_176052%2Foe-17-3-1256%2Epdf%3Fda%3D1%26id%3D176052%26seq%3D0%26mobile%3Dno&org=

·         Modeling diffuse reflectance from semi-infinite turbid media: application to the study of skin optical properties,
G. Zonios and A. Dimou,
Opt. Express 14, 8661-8674 (2006)
http://www.opticsinfobase.org/vjbo/fulltext.cfm?uri=oe-14-19-8661&id=105648
http://www.opticsinfobase.org/view_article.cfm?gotourl=http%3A%2F%2Fwww%2Eopticsinfobase%2Eorg%2FDirectPDFAccess%2F524EEC74-BF62-4435-E9EE2475328176B4_105648%2Foe-14-19-8661%2Epdf%3Fda%3D1%26id%3D105648%26seq%3D0%26mobile%3Dno&org=

·         Melanin absorption spectroscopy: new method for noninvasive skin investigation and melanoma detection
G Zonios, A Dimou, I Bassukas
Journal of Biomedical Optics 13(1), 2008
http://www.seas.harvard.edu/ekaxiras/pubs/Papers/JBiomOpt_13_014017_2008.pdf

 

Tsumura Papers:

·         Independent Component Analysis of Skin Color Image
Norimichi Tsumura, Hideaki Haneishi and Yoichi Miyake
CIC 2006
www.mi.tj.chiba-u.jp/~tsumura/Tsumura/papers/CIC6_ICA.pdf

·         Image-based skin color and texture analysis/synthesis by extracting hemoglobin and melanin information in the skin
Norimichi Tsumura Nobutoshi Ojima Kayoko Sato Mitsuhiro Shiraishi
Hideto Shimizu Hirohide Nabeshima Syuuichi Akazaki Kimihiko Hori Yoichi Miyake
Siggraph 2003
http://www.mi.tj.chiba-u.jp/~tsumura/Tsumura/projects/Siggraph2003/TsumuraSig03.pdf

 

Yudovsky Papers:

·         Rapid and Accurate Estimation of Blood Saturation, Melanin Content, and Epidermis Thickness from Spectral Diffuse Reflectance.
D. Yudovsky and L. Pilon
Applied Optics, Vol. 49, no. 10, pp. 1707–1719, 2010
http://www.seas.ucla.edu/~pilon/Publications/AO2010.pdf

·         Retrieving Skin Properties From In Vivo Diffuse Reflectance Measurements on Human Skin
D. Yudovsky and L. Pilon
Journal of Biophotonics, Vol. 4, No.5, pp.305-314, 2011
http://www.seas.ucla.edu/~pilon/Publications/JBP2011-1.pdf

·         Liveness detection for iris recognition using multispectral images
Rui Chen, Xirong Lin, Tianhuai Ding
Pattern Recognition Letters Volume 33, Issue 12, 1 September 2012, Pages 1513-1519
https://www.sciencedirect.com/science/article/abs/pii/S0167865512001262

·        


Lecture 12 – Biometrics via Hyperspectral imaging    (19/6/24b)  
 

      Liveliness detection (determining live vs fake person)

·         Liveness detection for iris recognition using multispectral images
Rui Chen, Xirong Lin, Tianhuai Ding
Pattern Recognition Letters Volume 33, Issue 12, 1 September 2012, Pages 1513-1519
https://www.sciencedirect.com/science/article/abs/pii/S0167865512001262

 

·         Face Liveness Detection by Learning Multispectral Reflectance Distributions
Zhiwei Zhang, Dong Yi, Zhen Lei, Stan Z. Li
Face and Gesture 2011
https://www.researchgate.net/publication/224238158_Face_liveness_detection_by_learning_multispectral_reflectance_distributions

·         The imaging issue in an automatic face/disguise detection system  (2 wavelengths)
Ioannis Pavlidis and Peter Symosek,
Proceedings of IEEE workshop on Computer Vision Beyond the Visible Spectrum:
Methods and Applications, 2000
https://www.cpl.uh.edu/images/publication_files/C13.pdf

·         Masked fake face detection using radiance measurements (2 wavelengths)
Youngshin Kim, Jaekeun Na, Seongbeak Yoon, and Juneho Yi,
Journal of the Optical Society of America A, vol. 26, no. 4, 2009
https://pdfs.semanticscholar.org/6e42/5c9315bf9a4643fb8aa33cd2efaf5a650471.pdf


·         Fingerprint detection – skip

Spectroscopically enhanced method and system for multi-factor biometric authentication.
Davar P, 2008, IEICE Trans Inf Syst E91-D(5):1369–1379
https://www.jstage.jst.go.jp/article/transinf/E91.D/5/E91.D_5_1369/_pdf

 

Lecture 13 – Emotion and stress detection using HI    (skip) 
 

·         Remote sensing of stress using Electro-optics imaging technique
Yuen, P., Chen, T., Hong, K., Tsitiridis, A., Jackman, J., James, D., Richardson,
M. A., Oxford, W., Piper, J., Thomas, F. and Lightman, S.

Proceedings of SPIE - The International Society for Optical Engineering 7486 · September 2009
https://pdfs.semanticscholar.org/c861/ad6178791552fd2b47663a26aeff453cb25a.pdf


Full paper:
https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/7502/PhD%20thesisV11bfinal%20correction.pdf?sequence=1&isAllowed=y

·         Biometric study using hyperspectral imaging during stress

Sheela Nagaraj, Shafik Quoraishee, Gabriel Chan, Kenneth R. Short
Proceedings Volume 7674, Smart Biomedical and Physiological Sensor Technologies VII; 76740K (2010) 

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7674/76740K/Biometric-study-using-hyperspectral-imaging-during-stress/10.1117/12.850282.short?SSO=1

·         Detecting Happiness Using Hyperspectral Imaging Technology

Min Hao, Guangyuan Liu, Anu Gokhale, Ya Xu, and Rui Chen
Computational Intelligence and Neuroscience Volume 2019

https://www.hindawi.com/journals/cin/2019/1965789/

 

 

 

Lecture 14 – Medical studies using HI    (3.7.24a+3.7.24b)

Medical imaging as well as skin 9melanoma detection etc)

·        Visible reflectance hyperspectral imaging: characterization of a noninvasive,
in vivo system for determining tissue perfusion.
Zuzak, K. J., Schaeberle, M. D. and Lewis, E. N.
Anal. Chem., 2002, 74, 2021–2028.
https://pdfs.semanticscholar.org/d0f8/ae354e09542a13c62a7b4832fe878908229d.pdf

·        Zuzak, K., Gladwin, M., Cannon, R. and Levin, I.
Imaging hemoglobin oxygen saturation in sickle cell disease patients using
noninvasive visible reflectance hyperspectral techniques: effects of nitric oxide.
Am. J. Physiol. Heart Circ. Physiol., 2003, 285, H1183–H1189.
https://www.semanticscholar.org/paper/Imaging-hemoglobin-oxygen-saturation-in-sickle-cell-Zuzak-Gladwin/26492d5a908940f74ceb7805468ee9bb0cae6c19

·        Differentiation of normal skin and melanoma using high resolution hyperspectral imaging
Dicker, D.T.,  Lerner, J.,  Van Belle, P.,  Barth, S.F.,  Guerry IV, D.,  Herlyn, M.,  Elder, D.E.,  El-Deiry, W.S.
Cancer Biology and Therapy Volume 5, Issue 8, August 2006, Pages 1033-1038
https://www.scopus.com/record/display.uri?eid=2-s2.0-33751195543&origin=inward&txGid=2fd579ccaaa079e889944d86c8ec006b

·        Active DLP Hyperspectral Illumination: A Noninvasive, in Vivo, System Characterization

Visualizing Tissue Oxygenation at Near Video Rates
Karel J. Zuzak, Robert P. Francis, Eleanor F. Wehner, Maritoni Litorja, Jeffrey A. Cadeddu,
and Edward H. Livingston
Anal. Chem., 2011, 83 (19), pp 7424–7430
https://pubs.acs.org/doi/abs/10.1021/ac201467v

 

·        Characterization of a Near-Infrared Laparoscopic Hyperspectral Imaging System

for Minimally Invasive Surgery
Karel J. Zuzak, Sabira C. Naik, George Alexandrakis, Doyle Hawkins, Khosrow Behbehani, and Edward H. Livingston
Anal. Chem., 2007, 79 (12), pp 4709–4715

https://pubs.acs.org/doi/pdf/10.1021/ac070367n

·      Medical - Ulcer    
      http://www.seas.ucla.edu/~pilon/TemporalUlcerDevelopment+Healing.htm

·      Medical - Colon
Lu G., Halig L., Wang D., Qin X., Chen Z. G., Fei B. Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging. Journal of Biomedical Optics . 2014;19(10) doi: 10.1117/1.JBO.19.10.106004.106004
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4183763/

 




Lecture 16 – Art and Hyperspectral images   (10/7/24a) 

Underpinting, pigment identification, forgery detection

·           Hyperspectral Imaging for Art Conservation  - See citations within: https://surfaceoptics.com/applications/art-antiquities-conservation-hyperspectral/

·         Chapter 5 Hyperspectral Imaging: A New Technique for the Non-Invasive Study of Artworks https://www.sciencedirect.com/science/article/abs/pii/S1871173107800078

·         Reflectance Hyperspectral Imaging for Investigation of Works of Art: Old Master Paintings and Illuminated Manuscripts
https://pubs.acs.org/doi/10.1021/acs.accounts.6b00048

·          

 

Lecture 17 – Hyperspectral images - Applications   (10/7/24b  )

·           1) Meat Quality

·           2) Opthamology

·           3) Medical - Ulcer    
      http://www.seas.ucla.edu/~pilon/TemporalUlcerDevelopment+Healing.htm

·           3b) Medical - Colon
Lu G., Halig L., Wang D., Qin X., Chen Z. G., Fei B. Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging. Journal of Biomedical Optics . 2014;19(10) doi: 10.1117/1.JBO.19.10.106004.106004
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4183763/

·          

·           4) Vehicle Tracking ?? http://citeseerx.ist.psu.edu/viewdoc/summary?

·           5) Vegetable Monitoring

·           6) Ship Detection

·           7) ancient texts Ancient Greek text concealed on the back of unrolled papyrus revealed through shortwave-infrared hyperspectral imaging
https://www.science.org/doi/10.1126/sciadv.aav8936

·       Agriculture:

Hyperspectral image analysis techniques for the detection and classification of the

early onset of plant disease and stress. Amy Lowe, Nicola Harrison and Andrew P French,      Plant Methods201713:80
 https://plantmethods.biomedcentral.com/articles/10.1186/s13007-017-0233-z#Sec4

 

Detection of Environmental Change Using Hyperspectral Remote Sensing

at Olkiluoto Repository Site, Jyrki Tuominen Tarmo Lipping, 2011

http://www.posiva.fi/files/1502/WR_2011-26_web.pdf

 

Highly sensitive image-derived indices of water-stressed plants using hyperspectral

imaging in SWIR and histogram analysis

David M. Kim, Hairong Zhang, Haiying Zhou, Tommy Du, Qian Wu, Todd C. Mockler & Mikhail Y. Berezin,  Scientific Reports volume 5, Article number: 15919 (2015)

https://www.nature.com/articles/srep15919

 

Detecting and Monitoring Plant Nutrient Stress Using Remote Sensing Approaches: A Review

Chong Yen Mee, Siva Kumar Balasundram and Ahmad Husni Mohd Hanif

Asian Journal of Plant Sciences Volume 16 (1): 1-8, 2017 https://scialert.net/fulltextmobile/?doi=ajps.2017.1.8

 

 

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Hyperspectral imaging using Machine Learning / Deep Learning 
 

·        Hyperspectral Image Classification With Deep Learning Models
Xiaofei Yang  ; Yunming Ye ; Xutao Li  ; Raymond Y. K. Lau  etal
IEEE Transactions on Geoscience and Remote Sensing,  Volume: 56 , Issue: 9 , Sept. 2018
https://ieeexplore.ieee.org/document/8340197

·        Deep Feature Extraction and Classification of Hyperspectral Images Based on
Convolutional Neural Networks

Yushi Chen, , Hanlu Jiang, Chunyang Li, Xiuping Jia, Pedram Ghamisi
IEEE Transactions on Geoscience and Remote Sensing, Volume: 54 , Issue: 10 , Oct. 2016
https://elib.dlr.de/106352/2/CNN.pdf

 

·         Hyperspectral Image Classification Using Convolutional Neural Networks and Multiple

Feature Learning

Qishuo Gao, Samsung Lim and Xiuping Jia
Remote Sensing 2018
https://www.mdpi.com/2072-4292/10/2/299

 

·         Machine learning based hyperspectral image analysis: A survey

Utsav B. Gewali, Sildomar T. Monteiro, Eli Saber

https://arxiv.org/abs/1802.08701  Feb 2019

 

·         Convolution Neural Network Based on Two-Dimensional Spectrum for Hyperspectral Image Classification
Hongmin Gao,1 Shuo Lin,1 Yao Yang,1 Chenming Li,1 and Mingxiang Yang2
https://www.hindawi.com/journals/js/2018/8602103/

·         Signoroni A., Savardi M., Baronio A., Benini S. Deep learning meets hyperspectral image analysis: a multidisciplinary review. Journal of Imaging . 2019;5:p. 52. doi: 10.3390/jimaging5050052.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320953/

·