Cui B G, Zhang J, Ma Y, et al. High-resolution image-assisted endmember extraction of hyperspectral image[J]. Journal of Remote Sensing, 2014, 18(1):192-205.[崔宾阁,张杰,马毅,等.高分辨率图像辅助提取高光谱图像端元[J].遥感学报,2014,18(1):192-205.] [DOI: 10.11834/jrs.20133067]
[2]
Boardman JW, Kruse F A, Green R O.Mapping target signatures via partial unmixing of AVIRIS data[C]//Proceedings of the 5th Annual JPL Airborne Earth Science Workshop. Pasadena, USA: JPL, 1995: 23-26.
[3]
Dowler S,Andrews M. On the Convergence of N-FINDR and Related Algorithms: To Iterate or Not to Iterate? [J].Geosciences and Remote Sensing Letters,2011, 8(1):4-8.[DOI: 10.1109/LGRS.2010.2049639]
[4]
NascimentoJ M P,BioucasDias J M.Vertex component analysis: a fast algorithm to unmixhyperspectraldata [J].IEEE Transactionson Geoscience and Remote Sensing,2005,43(4):898-910. [DOI: 10.1109/TGRS.2005.844293]
[5]
Gruninger J H,Ratkowski A J,Hoke M L.The sequential maximum angle convex cone(SMACC)endmembermodel [C]//Proceedings of SPIE.Orlando,FL,USA:SPIE,2004,5425(1): 5425-5432. [DOI: 10.1117/12.543794]
[6]
Li E S, Zhu X L, Zhou X M, et al. The development and comparison of endmember extraction algorithms using hyperspectral imagery[J]. Journal of Remote Sensing, 2011, 15(4):659-679.[李二森,朱述龙,周晓明,等.高光谱图像端元提取算法研究进展与比较[J].遥感学报,2011,15(4):659-679.]
[7]
Chen Z X, Wu W B. A review on endmember extraction algorithms based on the linear mixing model[J]. Science of Surveying and Mapping, 2008, 33(S1):49-51.[陈子玄,武文波.基于线性混合模型的端元提取方法综述[J].测绘科学,2008,33(S1):49-51.] [DOI: 10.3771/j.issn.1009-2307. 2008. 07.018]
[8]
Neville R A,Staenz K,Szeredi T.Automatic endmember extraction from hyperspectral data for mineral exploration[C]// The 21st Canadian Symposium.Ottawa,Canada: Remote Sensing,1999:21-24.
[9]
Lee DD,Seung H S.Learning the parts of objects by non-negative matrix factorization[J].Nature,1999,401(6755):788-791.
[10]
Yang K M, Liu S W, Wang L W, et al. An algorithm of spectral minimum shannon entroy on extracting endmember of hyperspectral image[J]. Spectroscopy and Spectral Analysis, 2014, 34(8): 2229-2233.[杨可明,刘士文,王林伟,等.光谱最小信息熵的高光谱影像端元提取算法[J].光谱学与光谱分析,2014,34(8):2229-2233.] [DOI: 10.3964/j.issn.1000 0593(2014)08 2229 05]
[11]
Zhang B, Sun X, Gao L R, et al. A method of endmember extraction in hyperspectral remote sensing image based on discrete particle swarm optimization(D-PSO)[J]. Spectroscopy and Spectral Analysis, 2011,31(9): 2455-2461.[张兵,孙旭,高连如,等.一种基于离散粒子群优化算法的高光谱图像端元提取方法[J].光谱学与光谱分析,2011,31(9):2455-2461.] [DOI: 10.3964/j.issn.1000-0593(2011)09-2455-07]
[12]
Eusuff M,Lansey K E.Optimization of water distribution network design using the shuffled frog leaping algorithm[J].Water Resources Planning and Management,2003,129(3):210-225.[DOI:10.1061/(ASCE)0733-9496(2003)129:3(210)]
[13]
Kennedy J,Eberhart R.Particle swarm optimization[C]//Proceedings of the IEEE International Conference.Perth,Western Australia: Neural Networks,1995,4:1942-1948. [DOI: 10.1109/ICNN.1995.488968]
[14]
Kennedy J.The particle swarm: social adaptation of knowledge[C]//Proceedings of IEEE International Conference. Indianapolis,Indiana:Evolu-tionary Computation,1997, 303-308. [DOI: 10. 1109/ICEC.1997.592326]
[15]
Wang L G,Liu D F,Wang Q M.Geometric method of fully constrained least squares linear spectral mixture analysis[J].IEEE Transactions on Geosciences and Remote Sensing,2013,51(6):3558-3566. [DOI: 10.1109/TGRS.2012.2225841]
[16]
Chang C,Du Q.Estimation of number of spectrally distinct signal sources in hyperspectral imagery[J]. IEEE Transactions on Geosciences and Remote Sensing,2004,42(3):608-619. [DOI: 10.1109/TGRS.2003.819189]
[17]
Green A A,Berman M,Switzer B,et al.A transformation for ordering multispectral data in terms of image quality with implications for noise removal[J].IEEE Transactions on Geosciences and Remote Sensing,1998,26(1):65-74. [DOI: 10.1109/36.3001]
