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Hyperspectral image classification phd thesis proposal

Hyperspectral image classification phd thesis proposal IEEE TGRS


Journals and Conference papers

For those of you who are interested in the fusion of LiDAR and hyperspectral data or the classification of hyperspectral images, we made our dataset public. The dataset was captured over Samford Ecological Research Facility (SERF), Queensland, Australia. The dataset is composed of hyperspectral and LiDAR data as well as their corresponding training and test samples. You may download the data from the following address:
https://figshare.com/articles/Main_zip/2007723

P. Ghamisi, Spectral and Spatial Classification of Hyperspectral Data, Ph.D. thesis, University of Iceland, 2015.
skemman.is/en/item/view/1946/20837

[B2] J. A. Benediktsson and P. Ghamisi, Spectral-Spatial Classification of Hyperspectral Remote Sensing Images, Artech House Publishers, INC, Boston, USA.
Spectral-Spatial Classification of Hyperspectral Remote Sensing Images

[B1] M. S. Couceiro and P. Ghamisi, Fractional Order Darwinian Particle Swarm Optimization: Applications and Evaluation of an Evolutionary Algorithm. Springer Verlag, London, 2015.
Fractional Order Darwinian Particle Swarm Optimization: Applications and Evaluation of an Evolutionary Algorithm (SpringerBriefs in Applied Sciences and Technology)

P. Ghamisi; R. Souza; J. A. Benediktsson; L. Rittner; R. Lotufo; X. X. Zhu, “Hyperspectral Data Classification Using Extended Extinction Profiles,” in IEEE Geoscience and Remote Sensing Letters. vol.PP, no.99, pp.1-5 doi: 10.1109/LGRS.2016.2600244

P. Ghamisi; Y. Chen; X. X. Zhu, “A Self-Improving Convolution Neural Network for the Classification of Hyperspectral Data,” in IEEE Geoscience and Remote Sensing Letters. vol.PP, no.99, pp.1-5 doi: 10.1109/LGRS.2016.2595108

Hyperspectral image classification phd thesis proposal Sensing, vol

[J18] Y. Chen, H. Jiang, C. Li, X. Jia and P. Ghamisi, “Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks,”

Y. Chen, H. Jiang, C. Li, X. Jia and P. Ghamisi, “Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 10, pp. 6232-6251, Oct. 2016.

[J17] P. Ghamisi ; R. Souza; J. A. Benediktsson; X. X. Zhu; L. Rittner; R. A. Lotufo, “Extinction Profiles for the Classification of Remote Sensing Data,”

P. Ghamisi; R. Souza; J. A. Benediktsson; X. X. Zhu; L. Rittner; R. A. Lotufo, “Extinction Profiles for the Classification of Remote Sensing Data,” in IEEE Transactions on Geoscience and Remote Sensing. vol.54, no.10, pp.5631 – 5645, 2016 [The most popular paper published by IEEE TGRS in July 2016]

[J16] P. Ghamisi, J. A. Benediktsson, and S. Phinn, “Landcover classification using both hyperspectral and lidar data,” International Journal of Image and Data Fusion, vol. 6, no. 3, pp. 189ᵬ 2015.

[J15] P. Ghamisi, A. ALi, M. S. Couceiro and J. A. Benediktsson, “A Novel Evolutionary Swarm Fuzzy Clustering Approach for Hyperspectral Imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, accepted.

S.Kargozar Nahavandy, P Ghamisi, L Kumar and M S Couceiro. Article: A Novel Adaptive Compression Technique for Dealing with Corrupt Bands and High Levels of Band Correlations in Hyperspectral Images Based on Binary Hybrid GA-PSO for Big Data Compression.

Hyperspectral image classification phd thesis proposal paper published by

International Journal of Computer Applications 109(8):18-25, January 2015.
ijcaonline.org/archives/volume109/number8/19208-0915

P. Ghamisi, M. S. Couceiro and J. A. Benediktsson, “A Novel Feature Selection Approach Based on FODPSO and SVM,” IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2935-2947, May 2015.
ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6980119&queryText%3Dghamisi

P. Ghamisi, M. Dalla Mura and J. A. Benediktsson, “A Survey on Spectral-Spatial Classification Techniques Based on Attribute Profiles,”IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2335-2353, May 2015.
ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6945376&queryText%3Dghamisi

P. Ghamisi, J. A. Benediktsson, Feature Selection Based on Hybridization of Genetic Algorithm and Particle Swarm Optimization, IEEE Geoscience and Remote Sensing Letter, 12(2), 309-313, Feb. 2015. DOI: 10.1109/LGRS.2014.2337320.
ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6866865&queryText%3Dghamisi

P. Ghamisi, J. A. Benediktsson, G. Cavallaro, A. Plaza, Automatic Framework for Spectral-Spatial Classification Based on Supervised Feature Extraction and Morphological Attribute Profiles, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(6): 2147-2160, 2014.
ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6729052&isnumber=4609444

P. Ghamisi, J.A. Benediktsson and J.R. Sveinsson, Automatic Spectral-Spatial Classification Framework Based onAttribute Profiles and Supervised Feature Extraction, IEEE Trans. on Geoscience and Remote Sensing, 52(9): 5771-5782, 2014.
ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6685827&isnumber=4358825

P. Ghamisi, J. A. Benediktsson, M. O. Ulfarsson, Spectral-Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields, IEEE Trans. Remote Sensing and Geoscience. 52(5): 2565-2574, 2014.
ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6532336&queryText%3DGHAMISI

P. Ghamisi, M. Couceiro, M. Fauvel and J. A. Benediktsson, Integration of Segmentation Techniques for Classification of Hyperspectral Images, IEEE Geosci. Remote Sensing Lett. 11(1): 342-346, 2014.
ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6545298&queryText%3DGHAMISI

P. Ghamisi, M. S. Couceiro, F. M.L. Martins and J. A. Benediktsson, Multilevel Image Segmentation Based on Fractional-Order Darwinian Particle Swarm Optimization, IEEE Trans. Geoscience and Remote Sensing, 52(5): 2382-2394, 2014.
ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6524014&queryText%3DGHAMISI

P. Ghamisi, F. Sepehrband, L. Kumar, M. S. Couceiro, Fernando M. L. Martins, A New Method for Compression of Remote Sensing Images Based on Enhanced Differential Pulse Code Modulation Transformation, ScienceAsia, 39(2013): 546-555, 2013.
scienceasia.org/content/viewabstract.php?ms=3923

P. Ghamisi, M. S. Couceiro, J. A. Benediktsson, N. M. F. Ferreira “An Efficient Method for Segmentation of Images Based on Fractional Calculus and Natural Selection”, Expert Systems with Application, 39 (2012) 12407-12417.
sciencedirect.com/science/article/pii/S0957417412006756

F. Sepehrband, P. Ghamisi, A. Mohammadzadeh, M. R. Sahebi, J. Choupan, “Efficient Adaptive Lossless Compression of Hyperspectral Data Using Enhanced DPCM”, International Journal of Computer Applications 35(4):6-11, December 2011.
research.ijcaonline.org/volume35/number4/pxc3976078.pdf

[J2] P. Ghamisi, “A Novel Method for Segmentation of Remote Sensing Images based on Hybrid GA-PSO”, International Journal of Computer Applications 29(2):7-14, September 2011.
research.ijcaonline.org/volume29/number2/pxc3874846.pdf

P. Ghamisi, A. Mohammadzadeh, M. R. Sahebi, F. Sepehrband and J. Choupan, “A Novel Real Time Algorithm for Remote Sensing Lossless Data Compression based on Enhanced DPCM”, International Journal of Computer Applications 27(1):47-53, August 2011.
ijcaonline.org/volume27/number1/pxc3874402.pdf

P. Ghamisi and J. A. Benediktsson, “Feature Selection of Hyperspectral Data by Considering the Integration of Genetic Algorithms and Particle Swarm Optimization,” in Proc. SPIE, Image and Signal Processing for Remote Sensing XX, 2014,pp. 92440J-92440J-6.

P. Ghamisi, J. A. Benediktsson, S. Phinn, Fusion of Hyperspectral and LiDAR Data in Classification of Urban Areas, IGARSS, Canada, 2014, [Invited paper].

P. Ghamisi, M. S. Couceiro and J. A. Benediktsson, FODSPO Based Feature Selection for Hyperspectral Remote Sensing Data, WHISPERS, Switzerland, 2014.

P. Ghamisi, M. S. Couceiro, J. A. Benediktsson, Classification of hyperspectral images with binary fractional order Darwinian PSO and random forests. Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 88920S (October 17, 2013); doi:10.1117/12.2027641.

P. Ghamisi, J. A. Benediktsson, M. O. Ulfarsson, THE SPECTRAL SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES BASED ON HIDDEN MARKOV RANDOM FIELD AND ITS EXPECTATION-MAXIMIZATION, IGARSS 2013, Melbourne, JULY 2013 (As the best paper in the student paper competition in IGARSS 2013)

P. Ghamisi, M. S. Couceiro, M. Fauvel, J. A. Benediktsson, SPECTRAL-SPATIAL CLASSIFICATION BASED ON INTEGRATED SEGMENTATION, IGARSS 2013, Melbourne, JULY 2013

P. Ghamisi, M. S. Couceiro and J. A. Benediktsson “Extending the fractional order Darwinian particle swarm optimization to segmentation of hyperspectral images”, Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85370F (November 8, 2012);
dx.doi.org/10.1117/12.978776

P. Ghamisi, M. S. Couceiro, N. M. F. Ferreira, L. Kumar, “Use of Darwinian Particle Swarm Optimization technique for the segmentation of Remote Sensing images,” Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International. vol. no. pp.4295-4298, 22-27 July 2012,
dx.doi.org/10.1109/IGARSS.2012.6351718

P. Ghamisi, F. Sepehrband, J. Choupan, M. Mortazavi, “Binary Hybrid GA-PSO based algorithm for compression of hyperspectral data,” Signal Processing and Communication Systems (ICSPCS), 2011 5th International Conference on. vol. no. pp.1-8, 12-14 Dec. 2011
dx.doi.org/10.1117/12.904727

P. Ghamisi, F. Sepehrband, J. Choupan, M. Mortazavi, Binary Hybrid GA-PSO based algorithm for compression of hyperspectral data, 2011 5th International Conference on Signal Processing and Communication Systems (ICSPCS), vol. no. pp.1-8, 12-14 Dec. 2011
dx.doi.org/10.1109/ICSPCS.2011.6140839

F. Sepehrband, P. Ghamisi, M. Mortazavi, J. Choupan, “Simple and Efficient Remote Sensing Image Transformation for Lossless Compression”. International Conference on Signal and InformationProcessing (ICSIP’10), Changsha, China, December, 2010. (Published).

F. Sepehrband, P. Ghamisi, M. Mortazavi and J. Choupan, “Simple and efficient remote sensing image transformation for lossless compression”, Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82854A (September 30, 2011);
dx.doi.org/10.1117/12.913262

P. Ghamisi, F. Sepehrband,A. Mohammadzadeh, M. Mortazavi, J. Choupan, “Fast and Efficient Algorithm for Real Time Lossless Compression of LiDAR rasterized data Based on Improving Energy Compaction”, The 6th IEEE GRSS and ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, JURSE’11, Munich, Germany, April 2011. (Published).


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