[1] 蓝金辉, 邹金霖, 郝彦爽, 等. 高光谱遥感影像混合像元分解研究进展[J]. 遥感学报, 2018, 22(1):13-27. LAN Jinhui, ZOU Jinlin, HAO Yanshuang, et al. Research progress on unmixing of hyperspectral remote sensing imagery[J]. Journal of Remote Sensing, 2018, 22(1):13-27. [2] 张春森, 郑艺惟, 黄小兵, 等. 高光谱影像光谱-空间多特征加权概率融合分类[J]. 测绘学报, 2015, 44(8):909-918. DOI:10.11947/j.AGCS.2015.20140544. ZHANG Chunsen, ZHENG Yiwei, HUANG Xiaobing, et al. Hyperspectral image classification based on the weighted probabilistic fusion of multiple spectral-spatial features[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(8):909-918. DOI:10.11947/j.AGCS.2015.20140544. [3] 王俊淑, 江南, 张国明, 等. 融合光谱-空间信息的高光谱遥感影像增量分类算法[J]. 测绘学报, 2015, 44(9):1003-1013. DOI:10.11947/j.AGCS.2015.20140388. WANG Junshu, JIANG Nan, ZHANG Guoming, et al. Incremental classification algorithm of hyperspectral remote sensing images based on spectral-spatial information[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(9):1003-1013. DOI:10.11947/j.AGCS.2015.20140388. [4] DELGADO J, MARTÍN G, PLAZA J, et al. Fast spatial preprocessing for spectral unmixing of hyperspectral data on graphics processing units[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(2):952-961. [5] PLAZA A, MARTÍNZE P, PÉREZ R, et al. Spatial/spectral endmember extraction by multidimensional morphological operations[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(9):2025-2041. [6] JIMÉNEZ L I, PLAZA J, PLAZA A. Efficient implementation of morphological index for building/shadow extraction from remotely sensed images[J]. Journal of Supercomputing, 2017, 73(1):482-494. [7] 方俊龙. 高光谱像元解混技术研究[D]. 杭州:杭州电子科技大学, 2016. FANG Junlong. Research on hyperspectral unmixing techniques[D]. Hangzhou:Hangzhou Dianzi University, 2016. [8] CHANG C I, PLAZA A. A fast iterative algorithm for implementation of pixel purity index[J]. IEEE Geoscience and Remote Sensing Letters, 2006, 3(1):63-67. [9] LU Xiaoqiang, WU Hao, YUAN Yuan, et al. Manifold regularized sparse NMF for hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(5):2815-2826. [10] HEYLEN R, PARENTE M, GADER P. A review of nonlinear hyperspectral unmixing methods[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(6):1844-1868. [11] CHANG C I, WU Chaocheng. Design and development of iterative pixel purity index[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(6):2676-2695. [12] ZARE A, GADER P, CASELLA G. Sampling piecewise convex unmixing and endmember extraction[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(3):1655-1665. [13] LI H C, CHANG C I. Recursive orthogonal projection-based simplex growing algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(7):3780-3793. [14] ZHANG Shaoquan, AGATHOS A, LI Jun. Robust minimum volume simplex analysis for hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(11):6431-6439. [15] LI H C, CHANG C I. Geometric simplex growing algorithm for finding endmembers in hyperspectral imagery[C]//Proceedings of 2016 IEEE International Geoscience and Remote Sensing Symposium. Beijing:IEEE, 2016. [16] 李琳, 孟令博, 孙康, 等. 基于代数余子式的N-FINDR快速端元提取算法[J]. 电子与信息学报, 2015, 37(5):1128-1134. LI Ling, MENG Lingbo, SUN Kang, et al. A fast N-FINDR algorithm based on cofactor of a determinant[J]. Journal of Electronics and Information Technology, 2015, 37(5):1128-1134. [17] GENG Xiurui, SUN Kang, JI Luyan, et al. Optimizing the endmembers using volume invariant constrained model[J]. IEEE Transactions on Image Processing, 2015, 24(11):3441-3449. [18] 徐君, 徐富红, 蔡体健, 等. 一种基于最大距离的纯像元指数端元提取算法[J]. 地球信息科学学报, 2015, 17(1):86-90. XU Jun, XU Fuhong, CAI Tijian, et al. A novel pure pixel index endmember extraction algorithm based on the maximum distance[J]. Journal of Geo-Information Science, 2015, 17(1):86-90. [19] CHANG C I, WU C C, LIU W, et al. A new growing method for simplex-based endmember extraction algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(10):2804-2819. [20] CHANG C I, WU Chaocheng, LO C S, et al. Real-time simplex growing algorithms for hyperspectral endmember extraction[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(4):1834-1850. [21] CHAN T H, CHI C Y, HUANG Y M, et al. A convex analysis-based minimum-volume enclosing simplex algorithm for hyperspectral unmixing[J]. IEEE Transactions on Signal Processing, 2009,57(11):4418-4432. [22] LIU Junmin, ZHANG Jiangshe. A new maximum simplex volume method based on householder transformation for endmember extraction[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(1):104-118. [23] 王瀛, 梁楠, 郭雷. 一种基于修正扩展形态学算子的高光谱遥感图像端元提取算法[J]. 光子学报, 2012, 41(6):672-677. WANG Ying, LIANG Nan, GUO Lei. A hyperspectral remote sensing image endmember extraction algorithm based on modified extended-morphological operator[J]. Acta Photonica Sinica, 2012, 41(6):672-677. [24] SWAYZE G A. The hydrothermal and structural history of the cuprite mining district, southwestern Nevada:An integrated geological and geophysical approach[D]. Boulder:University of Colorado, 1997:399. [25] CLARK R N, SWAYZE G A. Automated spectral analysis:Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials:The USGS tricorder algorithm[C]//Proceedings of the 5th Annual JPL Airborne Earth Science Workshop. Pasadena:JPL Publication, 1995. [26] BIOUCAS-DIAS J M, NASCIMENTO J M P. Hyperspectral Subspace Identification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(8):2435-2445. |