• Acta Optica Sinica
  • Vol. 34, Issue 11, 1128001 (2014)
Wang Lijiao1、*, Li Xiaorun1, and Zhao Liaoying2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3788/aos201434.1128001 Cite this Article Set citation alerts
    Wang Lijiao, Li Xiaorun, Zhao Liaoying. Fast Implement of the Simplex Growing Algorithm for Endmember Extraction[J]. Acta Optica Sinica, 2014, 34(11): 1128001 Copy Citation Text show less
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    [2] Junmin Liu, Jiangshe Zhang. A new maximum simplex volume method based on householder transformation for endmember extraction [J]. IEEE Trans Geosciences and Remote Sensing, 2006, 44(10): 104-118.

    [3] J W Boardman, F A Kruse, R O Green. Mapping target signatures via partial unmixing of AVIRIS data [C]. Proc Summ JPL Airborne Earth Science Workshop, Pasadena, CA, 1995. 23-26.

    [4] Zhao Chunhui, Qi Bin, Wang Yulei. An improved N-FINDR hyperspectral endmember extraction algorithm [J]. Journal of Electronics & Information Technology Feb, 2012, 34(2): 499-503.

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    [6] Chein-I Chang, Chao-Cheng Wu, Wei-min Liu, et al.. A new growing method for simplex-based endmember extraction algorithm [J]. IEEE Trans Geosciences and Remote Sensing, 2006, 44(10): 2804-2819.

    [7] M D Craig. Minimum-volume transforms for remotely sensed data [J]. IEEE Trans Geoscience and Remote Sensing, 1994, 32(3): 542-552.

    [8] J Li, J M Bioucas Dias. Minimum volume simplex analysis: A fast algorithm to unmix hyperspectral data [J]. Geosciences and Remote Sensing Symposium 2008. IGARSS 2008 IEEE International, 2008, 3: 250-253.

    [9] Wei Xiong, Chein-I Chang, Chao-Cheng Wu. Fast algorithms to implement N-FINDR for hyperspectral endmember extraction [J]. IEEE J Sel Top Appl Earth Observation and Remote Sensing, 2011, 3(4): 545-564.

    [10] Kang Sun, Xiurui Geng, Panshi Wang, et al.. A fast endmember extraction algorithm based on gram determinant [J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(6): 1124-1128.

    [11] Mahmoud ElMaghrbay, Reda Ammar, Sanguthevar-Rajasekaran. Fast GPU algorithms for endmember extraction from hyperspextral images [C]. Computers and Communication (ISCC), 2012 IEEE Symposium on, 2012. 631-636.

    [12] Liguo Wang, Fangjie Wei, Danfeng Liu, et al.. Fast implementation of maximum simplex volume-based endmember extraction in original hyperspectrral data space [J]. IEEE J Sel Top Appl Earth Observations and Remote Sensing, 2013, 2(6): 516-521.

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    [14] Wei Xia, Hanye Pu, Bin Wang, et al.. Triangular factorization-based simplex algorithms for hyperspectral unmixing [J]. IEEE Trans Geoscience and Remote Sensing, 2012, 50(11): 4420-4440.

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    [16] Li Xiaorun, Wu Xiaoming, Zhao Liaoying. Unsupervised nonlinear decomposition method of hyperspectral imagery [J]. Journal of Zhejiang University (Engineering Science), 2011, 45(4): 607-613.

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    CLP Journals

    [1] Yan Yang, Hua Wenshen, Cui Zihao, Wu Xishan, Liu Xun. Classification and Volume for Hyperspectral Endmember Extraction[J]. Laser & Optoelectronics Progress, 2018, 55(9): 93004

    Wang Lijiao, Li Xiaorun, Zhao Liaoying. Fast Implement of the Simplex Growing Algorithm for Endmember Extraction[J]. Acta Optica Sinica, 2014, 34(11): 1128001
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