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  1. J. Li, J. M. Bioucas-Dias, A. Plaza and L. Liu. Robust Collaborative Nonnegative Matrix Factorization for Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 10, % pp. 6076-6090, Oct. 2016. doi: 10.1109/TGRS.2016.2580702. (Download Matlab Demo)
  2. X. Xu, J. Li, X. Huang, M. Dalla Mura and A. Plaza. Multiple Morphological Component Analysis Based Decomposition for Remote Sensing Image Classification. IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 5, pp. 3083-3102, May 2016
  3. Z. Wu, Y. Li, A. Plaza, J. Li, F. Xiao and Z. Wei. Parallel and Distributed Dimensionality Reduction of Hyperspectral Data on Cloud Computing Architectures. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, accepted for publication, 2016
  4. S. Zhang, J. Li, K. Liu, C. Deng, L. Liu and A. Plaza. Hyperspectral Unmixing Based on Local Collaborative Sparse Regression. IEEE Geoscience and Remote Sensing Letters, accepted for publication, 2016
  5. B. Song, P. Li, J. Li and A. Plaza. One-Class Classification of Remote Sensing Images Using Kernel Sparse Representation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 4, pp. 1613-1623, April 2016
  6. J. Liu, Z. Wu, J. Li, A. Plaza and Y. Yuan. Probabilistic Kernel Collaborative Representation for Spatial-Spectral Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 4, pp. 2371-2384, April 2016
  7. J. Li, M. Khodadadzadeh, A. Plaza, X. Jia and J. M. Bioucas-Dias. A Discontinuity Preserving Relaxation Scheme for Spectral-Spatial Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 2, pp. 625-639, February 2016
  8. J. Li, A. Agathos, D. Zaharie, J. M. Bioucas Dias, A. Plaza, and X. Li, Minimum Volume Simplex Analysis: A Fast Algorithm for Linear Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 9, pp. 5067-5082, September 2015 (Download Matlab Demo)
  9. Y. Xu, Z. Wu, J. Li, A. Plaza and Z. Wei. Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation. IEEE Transactions on Geoscience and Remote Sensing, no. 4, pp. 1990-2000, April 2016
  10. Alim Samat, J. Li, Sicong Liu, Peijun Du, Zelang Miao, Jieqiong Luo, Improved hyperspectral image classification by active learning using pre-designed mixed pixels, Pattern Recognition, Available online 25 September 2015, ISSN 0031-3203, http://dx.doi.org/10.1016/j.patcog.2015.08.019.
  11. Y. Liu, J. Li and A. Plaza. Spectrometer-Driven Spectral Partitioning for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 2, pp. 668-680, February 2016.
  12. Shen, Q.; Li, J.; Zhang, F.; Sun, X.; Li, J.; Li, W.; Zhang, B. Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance. Remote Sens. 2015, 7, 14731-14756.
  13. J. Li, I. Dopido, P. Gamba and A. Plaza. Complementarity of Discriminative Classifiers and Spectral Unmixing Techniques for the Interpretation of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2899-2912, May 2015
  14. J. Li, X. Huang, P. Gamba, J. Bioucas, L. Zhang, J. Benediksson, and A. Plaza. Multiple Feature Learning for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, vol.53, no.3, pp.1592-1606, March 2015. Matlab Demo Available.. Codes for Attribute Profiles. Please read ReadMe Before using this demo, which is under the terms and policies by the Original Authors..
  15. Zhaohui Xue, Peijun Du, J. Li, and Hongjun Su. Simultaneous Sparse Graph Embedding for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, vol.53, no.11, pp.6114-6133, Nov. 2015
  16. Shen, Q.; Li, J.; Zhang, F.; Sun, X.; Li, J.; Li, W.; Zhang, B. Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance. Remote Sens. 2015, 7, 14731-14756.
  17. Z. Wu, J. Liu, A. Plaza, J. Li and Z. Wei. GPU Implementation of Composite Kernels for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 9, pp. 1973-1977, September 2015
  18. M. Khodadadzadeh, J. Li, S. Prasad and A. Plaza. Fusion of Hyperspectral and LiDAR Remote Sensing Data Using Multiple Feature Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 2971-2983, June 2015
  19. Y Wu, J Li, L Gao, X. Tan, and B. Zhang. "Graphics processing unit¨Caccelerated computation of the Markov random fields and loopy belief propagation algorithms for hyperspectral image classification," J. Appl. Remote Sens., 9(1), 097295 (2015). doi:10.1117/1.JRS.9.097295.
  20. Peijun Du, Zhaohui Xue, J. Li, and Antonio Plaza, Learning Discriminative Sparse Representations for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 6, pp. 1089-1104, June 2015.
  21. Z. Wu, Q. Wang, A. Plaza, J. Li, L. Sun, and Z. Wei. Real-Time Implementation of the Sparse Multinomial Logistic Regression for Hyperspectral Image Classification on GPUs. IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 7, pp. 1456-1460, July 2015.
  22. Z. Wu, Q. Wang, A. Plaza, J. Li, L. Sun and Z. Wei. Parallel Spatial-Spectral Hyperspectral Image Classification with Sparse Representation and Markov Random Fields on GPUs. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 2926-2938, June 2015.
  23. Z. Wu, Q. Wang, A. Plaza, J. Li, J. Liu and Z. Wei. Parallel Implementation of Sparse Representation Classifiers for Hyperspectral Imagery on GPUs. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 2912-2925, June 2015
  24. L. Gao, J. Li, M. Khodadadzadeh, A. Plaza, B. Zhang, Z. He, and H. Yan. Subspace-Based Support Vector Machines for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, vol.12, no.2, pp.349,353, Feb. 2015
  25. L. Gao, J. Gao, J. Li, A. Plaza, L. Zhuang, X. Sun, and B. Zhang. Multiple algorithm integration based on ant colony optimization for endmember extraction from hyperspectral imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI:10.1109/JSTARS.2014.2371615, 2015
  26. L. Zhuang, B. Zhang, L. Gao, J. Li and A. Plaza. Normal endmember spectral unmixing method for hyperspectral imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI:10.1109/JSTARS.2014.2360888, 2015
  27. J. Liang, X. Liu, K. Huang, X. Li, X. Shi, Y. Chen, and J. Li, Improved snow depth retrieval by integrating microwave brightness temperature and visible/infrared reflectance. Remote Sensing of Enviroment, Remote Sensing of Environment. 156: 500-509, 2015.
  28. Z. Xue, J. Li, L. Cheng, and P. Du. Spectral-Spatial Classification of Hyperspectral Image via Morphological Component Analysis Based Image Separation. IEEE Transactions on Geoscience and Remote Sensing, Vol. 53, No. 1, pp 70-84, 2015
  29. J. Li, P. Gamba, and A. Plaza. A Novel Semi-Supervised Method for Obtaining Fine Resolution Urban Extents Exploiting Coarser Resolution Maps. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, no.10, pp.4276,4287, Oct. 2014
  30. A. Agathos, J. Li, D. Petcu and A. Plaza. Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2281-2296, June 2014
  31. I. Dopido, J. Li, A. Plaza and P. Gamba. A New Hybrid Strategy Combining Semi-Supervised Classification and Unmixing of Hyperspectral Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, no.8, pp.3619,3629, Aug. 2014
  32. Y. Wu, L. Gao, B. Zhang, H. Zhao, and J. Li. Real-time implementation of optimized maximum noise fraction transform for feature extraction of hyperspectral images. Journal of Applied Remote Sensing, 8(1): 084797, 2014.
  33. L. Gao, Q. Guo, A. Plaza, J. Li, and B. Zhang. Probabilistic anomaly detector for remotely sensed hyperspectral data. Journal of Applied Remote Sensing, 8(1): 083538, 2014.
  34. L. Ni, L. Gao, S. Li, J. Li, and B. Zhang. Edge-constrained Markov random field classification by integrating hyperspectral image with LiDAR data over urban areas. Journal of Applied Remote Sensing, 8(1): 085089, 2014.
  35. X. Huang, X. Guan, J. A. Benediktsson, L. Zhang, J. Li, A. Plaza and M. Dalla Mura. Multiple Morphological Profiles from Multicomponent Base Images for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 12, pp. 4653-4669, December 2014
  36. M. Khodadadzadeh, J. Li, A. Plaza, and J. M. Bioucas-Dias. A Subspace-Based Multinomial Logistic Regression for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 12, pp. 2105-2109, December 2014
  37. M. Khodadadzadeh, J. Li, A. Plaza, H. Ghassemian, J. M. Bioucas-Dias and X. Li. Spectral-Spatial Classification of Hyperspectral Data Using Local and Global Probabilities for Mixed Pixel Characterization. IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 10, pp. 6298-6314, October 2014
  38. S. Alim, P. Du, S. Liu, J. Li, L.-Ch. Liang. E2LMs: Ensemble Extreme Learning Machines for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, no.4, pp.1060-1069, April 2014
  39. Q. Guo, B. Zhang, Q. Ran, L. Gao, J. Li and A. Plaza. Weighted-RXD and Linear Filter-Based RXD: Improving Background Statistics Estimation for Anomaly Detection in Hyperspectral Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2351-2366, June 2014.
  40. B. Zhang, Y. Liu, W. Zhang, L. Gao, J. Li, J. Wang, X. Li. Analysis of the Proportion of Surface Reflected Radiance in Mid-infrared Absorption Bands. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, no.6, pp. 2639-2464, June 2014
  41. B. Song, J. Li M. Dalla Mura, P. Li, A. Plaza, J. M. Bioucas Dias, J. A. Benediktsson and J. Chanussot. Remotely Sensed Image Classification Using Sparse Representations of Morphological Attribute Profiles. IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 8, pp. 5122-5136, August 2014
  42. J. Li, P. R. Marpu, A. Plaza, J. M. Bioucas-Dias and J. A. Benediktsson. Generalized Composite Kernel Framework for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 9, pp. 4816-4829, 2013. New Demo for Generalized Composite Kernel framework using Multinomial logistic Regression (MLR GCK) and Composite Kernel with Support Vector Machines (SVM CK) are available.(DEMO MLR-GCK and SVM-CK, Matlab Codes)
  43. J. Li J. M. Bioucas-Dias and A. Plaza. Spectral-Spatial Classification of Hyperspectral Data Using Loopy Belief Propagation and Active Learning. IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 2, pp. 844-856, 2013. (Updated Matlab Code NEW DEMO for Belief Propagation, Spectral Spatial Active Learning)
  44. J. Li J. M. Bioucas-Dias and A. Plaza. Semi-Supervised Hyperspectral Image Classification Using Soft Sparse Multinomial Logistic Regression. IEEE Geoscience and Remote Sensing Letters, vol.10, no. 2, pp. 318-322, 2013.
  45. I. Dopido, J. Li P. R. Marpu, A. Plaza, J. M. Bioucas-Dias and J. A. Benediktsson. Semi-Supervised Self-Learning for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 9, pp. 4032-4044, 2013.
  46. J. Li J. Bioucas-Dias and A. Plaza. Spectral-Spatial Hyperspectral Image Segmentation Using Subspace Multinomial Logistic Regression and Markov Random Fields. IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 3, pp. 809-823, 2012. (NEW Demo for MLRsubMLL matlab code for windows)
  47. J. Li J. Bioucas-Dias and A. Plaza. Hyperspectral Image Segmentation Using a New Bayesian Approach with Active Learning. IEEE Transactions on Geoscience and Remote Sensing.vol.49, no.10, pp.3947-3960, Oct. 2011. ( matlab code for windows)
  48. J. Li J. Bioucas-Dias and A. Plaza. Semi-Supervised Hyperspectral Image Segmentation Using Multinomial Logistic Regression with Active Learning. IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 11, pp. 4085-4098, 2010. (matlab code for windows)
  49. Jun Li, Peijun Li. Determination of the optimal wavelet decomposition level for hyperspectral imagery. Progress in Natural Science, Vol. 17, Number 11, pp, 1500-1508. Nov 2007 (in Chinese)
  1. J. Li and A. Plaza. Hyperspectral Image Processing: Methods and Approaches, in Remote Sensing Handbook, Volume I: Data Characterization, Classification and Accuracies. Edited by P. Thenkabail, Taylor and Francis, October 2, 2015 by CRC Press Reference - 678 Pages - 336 Color ISBN 9781482217865 - CAT# K22125.
  1. X.Xu, J. Li, M. Dalla. REMOTE SENSING IMAGE CLASSIFICATION BASED ON MULTIPLE MORPHOLOGICAL COMPONENT ANALYSIS. IEEE Geoscience and Remote Sensing Symposium (IGARSS'15), Milan, Italy, 2015.
  2. M. Khodadadzadeh, J. Li, A. Plaza and J. M. Bioucas-Dias. Hyperspectral Image Classification Based on Union of Subspaces. Proceedings of the Joint Urban Remote Sensing Conference (URBAN'15), Lausanne, Switzerland, 2015
  3. Y. Liu, J. Li and A. Plaza. Class-Oriented Spectral Partitioning for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Symposium (IGARSS'15), Milan, Italy, 2015
  4. M. Khodadadzadeh, A. Cuartero, J. Li and A. Plaza. Fusion of Hyperspectral and LiDAR Data Using Generalized Composite Kernels: A Case Study in Extremadura, Spain. IEEE Geoscience and Remote Sensing Symposium (IGARSS'15), Milan, Italy, 2015.
  5. Y. Li, Z. Wu, A. Plaza, J. Li, J. Wei, Z. Wei and J. Liu. Fast Principal Component Analysis for Hyperspectral Imaging Based on Cloud Computing. IEEE Geoscience and Remote Sensing Symposium (IGARSS'15), Milan, Italy, 2015.
  6. M. Khodadadzadeh, J. Li, A. Plaza and J. M. Bioucas-Dias. Hyperspectral Image Classification Based on Union of Subspaces. Proceedings of the Joint Urban Remote Sensing Conference (URBAN'15), Lausanne, Switzerland, 2015
  7. J. Li, J. M. Bioucas-Dias and A. Plaza. J. Li, J. M. Bioucas-Dias, A. Plaza and L. Liu. Robust Collaborative Nonnegative Matrix Factorization for Hyperspectral Unmixing (R-CoNMF). IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'15),Tokyo, Japan, 2015. Download here: arxiv link
  8. A. Agathos, J. Li, J. M. Bioucas-Dias and A. Plaza. Robust Minimum Volume Simplex Analysis for Hyperspectral Unmixing. European Signal Processing Conference (EUSIPCO'14), Lisbon, Portugal, 2014
  9. M. Khodadadzadeh, J. Li, A. Plaza, P. Gamba, J. A. Benediktsson and J. M. Bioucas-Dias. A New Framework for Hyperspectral Image Classification Using Multiple Spectral and Spatial Features. IEEE Geoscience and Remote Sensing Symposium (IGARSS'14), Quebec City, Canada, 2014
  10. Y. Liu, J. Li, A. Plaza, J. M. Bioucas-Dias, P. G. Rodriguez and A. Cuartero. Spectral Partitioning for Hyperspectral Remote Sensing Image Classification. IEEE Geoscience and Remote Sensing Symposium (IGARSS'14), Quebec City, Canada, 2014
  11. J. Li, Y. Liu, A. Plaza and P. Du. Decision Fusion Based on Extended Spectrometer-Driven Spectral Partitioning for Hyperspectral Image Classification. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'14), Lausanne, Switzerland, 2014
  12. M. Khodadadzadeh, J. Li A. Plaza, H. Ghassemian and J. M. Bioucas-Dias. Spectral-Spatial Classification for Hyperspectral Data Using SVM and Subspace MLR. IEEE Geoscience and Remote Sensing Symposium (IGARSS'13), Melbourne, Australia, 2013
  13. B. Song, J. Li P. Li and A. Plaza. Decision Fusion Based on Extended Multi-Attribute Profiles for Hyperspectral Image Classification. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'13), Gainesville, Florida, 2013
  14. I. Dopido, J. Li A. Plaza and P. Gamba. Semi-Supervised Classification of Urban Hyperspectral Data Using Spectral Unmixing Concepts. Proceedings of the Joint Urban Remote Sensing Conference (URBAN'13), Sao Paulo, Brazil, 2013
  15. I. Dopido, J. Li P. Gamba and A. Plaza. Semi-Supervised Classification of Hyperspectral Data Using Spectral Unmixing Concepts. Tyrrhenian Workshop 2012 on Advances in Radar and Remote Sensing, Naples, Italy, 2012.
  16. J. Li J. Bioucas-Dias and A. Plaza. Semi-Supervised Discriminative Random Field for Hyperspectral Image Classification. Submitted to IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'12), Shanghai, China, 2012.
  17. I. Dopido, J. Li J. Bioucas-Dias and A. Plaza. A New Semi-Supervised Approach for Hyperspectral Image Classification with Different Active Learning Strategies. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'12), Shanghai, China, 2012.
  18. J. Li J. Bioucas-Dias and A. Plaza. Nonnegative Matrix Factorization with Collaborativity for Hyperspectral Unmixing. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'12), Shanghai, China, 2012.
  19. J. Li J. Bioucas-Dias and A. Plaza. Collaborative Nonnegative Matrix Factorization for Remotely Sensed Hyperspectral Unmixing. IEEE Geoscience and Remote Sensing Symposium (IGARSS'12), Munich, Germany, 2012.
  20. I. Dopido, J. Li A. Plaza and J. Bioucas-Dias. Semi-Supervised Active Learning for Urban Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Symposium (IGARSS'12), Munich, Germany, 2012.
  21. I. Dopido, J. Li and A. Plaza. Semi-Supervised Active Learning Approach for Hyperspectral Image Classification: Application to Multinomial Logistic Regression and Support Vector Machines. SPIE Optics and Photonics, Satellite Data Compression, Communication, and Processing Conference, San Diego, CA, 2012.
  22. J. Li J. Bioucas-Dias and A. Plaza. Semi-Supervised Hyperspectral Image Classification Using a New (Soft) Sparse Multinomial Logistic Regression Model. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing, 2011. (pdf)
  23. A. Villa, J. Li A. Plaza and J. Bioucas-Dias. A New Semi-Supervised Algorithm for Hyperspectral Image Classification Based on Spectral Unmixing Concepts. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing, 2011. (pdf)
  24. J. Li J. Bioucas-Dias and A. Plaza. A New Subspace Discriminant Analysis Approach for Supervised Hyperspectral Image Classification. IEEE International Geoscience and Remote Sensing Symposium (IGARSS'11), Vancouver, Canada, 2011. (pdf)
  25. J. Li A. Plaza and J. Bioucas-Dias. Integration of Hyperspectral Image Classification and Unmixing for Active Learning. International Symposium on Image and Data Fusion, Tengchong, China, 2011. (pdf)
  26. J. Li J. Bioucas-Dias, and Antonio Plaza. Supervised Hyperspectral image segmentation using active learning. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'10), Reykjavik, Iceland, 2010. (pdf)
  27. J. Li J. Bioucas-Dias and A. Plaza. Exploiting spatial information in semi-supervised hyperspectral image segmentation. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS'10), Reykjavik, Iceland, 2010. (pdf)
  28. J. Li J. Bioucas-Dias, and Antonio Plaza. Semi-supervised hyperspectral image segmentation. IEEE GRSS Workshop on Hyperspectral Image and Signal Processing (WHISPERS'09), Grenoble, France, 2009. (pdf)
  29. J. Li J. Bioucas-Dias, and Antonio Plaza. Semi-supervised hyperspectral classification and segmentation with discriminative learning. SPIE Europe Remote Sensing, Berlin Germany, 2009. (pdf)
  30. J. Li J. Bioucas-Dias, and Antonio Plaza. Semi-supervised hyperpsectral imge classification based on a Markov random field and sparse multinomial logistic regression. IEEE International Geoscience and Remote sensing Symposium IGARSS’2009, Cape Town, South Africa, 2009. (pdf)
  31. J. Li J. Bioucas-Dias, and Antonio Plaza. Hyperspectral image classification based on a fast Bregman sparse multinomial logistic regression algorithm. 6th EARSeL SIG IS Workshop'2009, Tel- Aviv, Israel, 2009. (pdf)
  32. J. Li J. Bioucas-Dias. Minimum volume simplex analysis: a fast algorithm to unmix hyperspectral data. IEEE International Geoscience and Remote sensing Symposium IGARSS’2008, Boston, USA, 2008. (pdf)