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A Hyperspectral Band Selection Based on Game Theory and Differential Evolution Algorithm

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G.Shaw and D.Manolakis, “Signal processing for hyperspectral image exploitation”, IEEE Signal Processing,Magazine, vol. 19, no. 1, 2002, pp. 12-16.10.1109/79.974715 Search in Google Scholar

L.Ge, B.Wang and L.M. Zhang, “Band selection based on band clustering for hyperspectral imagery”, Journal of Computer-Aided Design & Computer Graphics, vol. 24, no.11, 2012, pp. 1447-1454. Search in Google Scholar

X.S.Liu, L.Ge, B.Wang and L.M.Zhang, “An unsupervised band selection algorithm for hyperspectral imagery based on maximal information”, Journal of Infrared and Millimeter Waves, vol. 31, no. 2, 2012, pp. 166-176.10.3724/SP.J.1010.2012.00166 Search in Google Scholar

S.Padma and S.Sanjeevi, “Jeffries Matusita based Mixed-measure for Improved Spectral Matching in Hyperspectral Image Analysis”, International Journal of Applied Earth Observation and Geoinformation, vol. 32, 2014, pp. 138-151.10.1016/j.jag.2014.04.001 Search in Google Scholar

C.M.Li, Y.Wang, H.M.Gao and L.L.Zhang, “Band Selection for Hyperspectral Image Classification based on Improved Particle Swarm Optimization Algorithm”, Advanced Materials Research, vol. 889-890, 2014, pp. 1073-1077.10.4028/www.scientific.net/AMR.889-890.1073 Search in Google Scholar

P.Gurram and H.Kwon, “Coalition Game Theory based Feature Subset Selection for Hyperspectral Image Classification”, IEEE International Geoscience and Remote Sensing Symposium, Canada, 3446-3449, 2014.10.1109/IGARSS.2014.6947223 Search in Google Scholar

L.G.Wang and F.J.Wei, “Artificial physics optimization algorithm combined band selection for hyperspectral imagery”, Journal of Harbin Institute of Technology, vol. 45, no. 9, 2013, pp. 100-106. Search in Google Scholar

H.M.Gao, L.Z. Xu, C.M. Li, A.Y. Shi, F.C. Huang and Z.L.Ma, “A New Feature Selection Method for Hyperspectral Image Classification based on Simulated Annealing Genetic Algorithm and Choquet Fuzzy Integral”, Mathematical Problems in Engineering, 2013.10.1155/2013/537268 Search in Google Scholar

Y.M. Meng, W.X. Li, Q.W. Chen, X. Yu, K.Y. Zheng and G.C. Lu “An Improved Multiobjective Evolutionary Optimization Algorithm for Sugar Cane Crystallization”, International Journal on Smart Sensing and Intelligent Systems, vol. 9, No.2, 2016, pp.953-978.10.21307/ijssis-2017-903 Search in Google Scholar

C.S. Lee, “Multi-objective Game-theory Models for Conflict Analysis in Reservoir Watershed Management”, Chemosphere, Vol.87, no.6, 2012, pp. 608-613.10.1016/j.chemosphere.2012.01.01422284980 Search in Google Scholar

P.Gurram and H.Kwon, “Coalition game theory based feature subset selection for hyperspectral image classification”, IEEE International Geoscience and Remote Sensing Symposium, 3446-3449, 2014.10.1109/IGARSS.2014.6947223 Search in Google Scholar

M.Zamarripa, A.Aguirre, C.Mendez and A.Espuna, “Integration of Mathematical Programming and Game Theory for Supply Chain Planning Optimization in Multi-objective Competitive Scenarios”, 22nd European Symposium on Computer Aided Process Engineering, England, vol. 30, 2012, pp. 402-406.10.1016/B978-0-444-59519-5.50081-2 Search in Google Scholar

R.Storn and K.Price, “Differential evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces”, Journal of Global Optimization, vol. 11, no. 4, 1997, pp. 341-359.10.1023/A:1008202821328 Search in Google Scholar

K.M.Yang, S.W.Liu, L.W.Wang, J.Yang, Y.Y.Sun and D.D. He, “An Algorithm of Spectral Minimum Shannon Entropy on Extracting Endmember of Hyperspectral Image”, Spectroscopy and Spectral Analysis, vol. 34, no. 8, 2014, pp. 2229-2233. Search in Google Scholar

T.Castaings, B.Waske, J.A.Benediktsson and J.Chanussot, “On the Influence of Feature Reduction for the Classification of Hyperspectral Images based on the Extended Morphological Profile”, International Journal of Remote Sensing, vol. 31, no. 22, 2010, pp. 5921-5939.10.1080/01431161.2010.512313 Search in Google Scholar

Y.C.Huo, X.Z.Wang and Y.Z.Kou, “A binary differential evolution algorithm with hybrid encoding”, Journal of Computer Research and Development, vol. 44, no. 9, 2007,pp. 1476-1484.10.1360/crad20070905 Search in Google Scholar

J.P.Zhang, Y.Zhang, B.Zou and T.X.Zhou, “Fusion classification of Hyperspectral Image based on Adaptive Subspace Decomposition”, IEEE International Conference on Image Processing, Canada, vol. 3, 2000, pp. 472-475. Search in Google Scholar

D.D.Yang, L.C.Jiao, M.G.Gong and H.Yu, “Clone selection algorithm to solve preference multi-objective optimization”, Journal of Software, vol. 21, no. 1, 2010, pp. 14-33.10.3724/SP.J.1001.2010.03551 Search in Google Scholar

B.L.Chen, W.H.Zeng, Y.B.Lin and D.F.Zhang, “A New Local Search-Based Multiobjective Optimization Algorithm”, IEEE Transactions on Evolutionary Computation, vol. 19, no. 1, 2015, pp. 50-73.10.1109/TEVC.2014.2301794 Search in Google Scholar

eISSN:
1178-5608
Lingua:
Inglese
Frequenza di pubblicazione:
Volume Open
Argomenti della rivista:
Engineering, Introductions and Overviews, other