Unsupervised Hyperspectral Band Selection by Fuzzy Clustering With Particle Swarm Optimization

IEEE Geoscience and Remote Sensing Letters

Volumn 14, Issue 5, 2017, Pages 773-777

  Zhang, Mingyang ^a   Ma, Jingjing ^a   Gong, Maoguo ^a  

^a XIDIAN UNIVERSITY   (China)

Author keywords

Band selection; fuzzy clustering; hyperspectral image (HIS); particle swarm optimization (PSO)

Indexed keywords

FUZZY CLUSTERING; SPECTROSCOPY;

BAND SELECTION; CLUSTER CENTERS; HIGH QUALITY; HYPERSPECTRAL; LABEL INFORMATION; PSO ALGORITHMS; ROBUST PERFORMANCE; UNLABELED DATA;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 85017190995     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2017.2681118     Document Type: Article

References (23)

1. C.-I. Chang, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, vol. 1. New York, NY, USA: Springer, 2003.
2. G. Hughes, "On the mean accuracy of statistical pattern recognizers," IEEE Trans. Inf. Theory, vol. 14, no. 1, pp. 55-63, Jan. 1968.
3. J. Wang and C.-I. Chang, "Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 6, pp. 1586-1600, Jun. 2006.
4. W. Li, S. Prasad, J. E. Fowler, and L. M. Bruce, "Localitypreserving dimensionality reduction and classification for hyperspectral image analysis," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 4, pp. 1185-1198, Apr. 2012.
5. L. Zhang, Y. Zhong, B. Huang, J. Gong, and P. Li, "Dimensionality reduction based on clonal selection for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 4172-4186, Dec. 2007.
6. J. Feng, L. C. Jiao, X. Zhang, and T. Sun, "Hyperspectral band selection based on trivariate mutual information and clonal selection," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 7, pp. 4092-4105, Jul. 2014.
7. C.-I. Chang, Q. Du, T.-L. Sun, and M. L. G. Althouse, "A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 6, pp. 2631-2641, Nov. 1999.
8. Q. Wang, J. Lin, and Y. Yuan, "Salient band selection for hyperspectral image classification via manifold ranking," IEEE Trans. Neural. Netw. Learn. Syst., vol. 27, no. 6, pp. 1279-1289, Jun. 2016.
9. A. Martínez-Usó, F. Pla, J. M. Sotoca, and P. García-Sevilla, "Clusteringbased hyperspectral band selection using information measures," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 4158-4171, Dec. 2007.
10. C. Cariou, K. Chehdi, and S. Le Moan, "BandClust: An unsupervised band reduction method for hyperspectral remote sensing," IEEE Geosci. Remote Sens. Lett., vol. 8, no. 3, pp. 565-569, May 2011.
11. H. Su, H. Yang, Q. Du, and Y. Sheng, "Semisupervised band clustering for dimensionality reduction of hyperspectral imagery," IEEE Geosci. Remote Sens. Lett., vol. 8, no. 6, pp. 1135-1139, Nov. 2011.
12. S. Jia, Z. Ji, Y. Qian, and L. Shen, "Unsupervised band selection for hyperspectral imagery classification without manual band removal," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 5, no. 2, pp. 531-543, Apr. 2012.
13. H. Su, Q. Du, G. Chen, and P. Du, "Optimized hyperspectral band selection using particle swarm optimization," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 7, no. 6, pp. 2659-2670, Jun. 2014.
14. Y. Yuan, G. Zhu, and Q. Wang, "Hyperspectral band selection by multitask sparsity pursuit," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 2, pp. 631-644, Feb. 2015.
15. J. Feng, L. Jiao, F. Liu, T. Sun, and X. Zhang, "Unsupervised feature selection based on maximum information and minimum redundancy for hyperspectral images," Pattern Recognit., vol. 51, pp. 295-309, Mar. 2016.
16. M. Gong, M. Zhang, and Y. Yuan, "Unsupervised band selection based on evolutionary multiobjective optimization for hyperspectral images," IEEE Trans. Geosci. Remote Sens., vol. 54, no. 1, pp. 544-557, Jan. 2016.
17. H. Su, B. Yong, and Q. Du, "Hyperspectral band selection using improved firefly algorithm," IEEE Geosci. Remote Sens. Lett., vol. 13, no. 1, pp. 68-72, Jan. 2016.
18. C.-Y. Chen and F. Ye, "Particle swarm optimization algorithm and its application to clustering analysis," in Proc. ICNSC, vol. 2. 2004, pp. 789-794.
19. T. A. Runkler and C. Katz, "Fuzzy clustering by particle swarm optimization," in Proc. Int. Conf. Fuzzy Syst., 2006, pp. 601-608.
20. A. A. A. Esmin, R. A. Coelho, and S. Matwin, "A review on particle swarm optimization algorithm and its variants to clustering highdimensional data," Artif. Intell. Rev., vol. 44, no. 1, pp. 23-45, 2015.
21. A. Ma, Y. Zhong, and L. Zhang, "Adaptive multiobjective memetic fuzzy clustering algorithm for remote sensing imagery," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 8, pp. 4202-4217, Aug. 2015.
22. R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proc. 6th Int. Symp. Micro Mach. Human Sci., vol. 1. New York, NY, USA, 1995, pp. 39-43.
23. X. Geng, K. Sun, L. Ji, and Y. Zhao, "A fast volume-gradient-based band selection method for hyperspectral image," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 11, pp. 7111-7119, Nov. 2014.