A Hyperspectral Band Selection Based on Game Theory and Differential Evolution Algorithm
By:
References
- 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
- 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.
- 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
- 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
- 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
- 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
- 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.
- 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
- 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
- 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
- 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
- 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
- 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
- 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.
- 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
- 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
- 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.
- 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
- 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
DOI: https://doi.org/10.21307/ijssis-2017-948 | Journal eISSN: 1178-5608
Language: English
Page range: 1971 - 1990
Submitted on: Mar 18, 2016
Accepted on: Oct 19, 2016
Published on: Dec 1, 2016
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year
Keywords:
Related subjects:
© 2016 Aiye Shi, Hongmin Gao, Zhenyu He, Min Li, Lizhong Xu, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.