Computer Science ›› 2018, Vol. 45 ›› Issue (12): 251-254.doi: 10.11896/j.issn.1002-137X.2018.12.041
• Graphics, Image & Pattern Recognition • Previous Articles Next Articles
ZOU Li1, CAI Xi-biao1, SUN Jing2, SUN Fu-ming1
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[1]GOETZ A F,VANE G,SOLOMON J E,et al.Imaging spec-trometry for earth remote sensing[J].Science,1985,228(4704):1147-1153. [2]VANE G,GREEN R,CHRIEN T G,et al.The airborne visible/infrared imaging spectrometer(AVIRIS)[J].Remote Sensing of Environment,1993,44(2):127-143. [3]GREEN R,EASTWOOD M L,SARTURE C M,et al.Imaging spectroscopy and the airborne visible/infrared imaging spectrometer(AVIRIS)[J].Remote Sensing of Environment,1998,65(3):227-248. [4]LEE D D,SEUNG H S.Learning the parts of objects by non-ne-gative matrix factorization[J].Nature,1999,401(6755):788-791. [5]TONG L,ZHOU J,QIAN Y T.Nonnegative Matrix Factorization Based Hyperspectral Unmixing with Partially Known Endmembers[J].IEEE Transactions on Geoscience and Remote Sensing,2016,54(11):6531-6544. [6]YU Y,GUO S,SUN W D.Minimum distance constrained nonnegative matrix factorization for the endmember extraction of hyperspectral images[C]∥Proceeding of Remote Sensing and GIS Data Processing and Applications.Wuhan,2007:6790151-6790159. [7]JIA S,QIAN Y T,JI X,et al.Hyperspectral Unmixing Algorithm Based on spectral and spatial characteristics[J].Journal of Shenzhen University(Science & Engineering),2009,26(3):162-167.(in Chinese) 贾森,钱沄涛,纪霞,等.基于光谱和空间特性的高光谱解混方法[J].深圳大学学报(理工版),2009,26(3):162-167. [8]YANG S Y,ZHANG X T,YAO Y G,et al.Geometric Nonnegative Matrix Factorization (GNMF) for Hyperspectral Unmixing[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sening,2015,8(6):2696-2703. [9]WANG W H,QIAN Y T,TANG Y Y.Hypergraph-Regularized Sparse NMF for Hyperspectral Unmixing[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sening,2016,9(2):681-694. [10]YUAN Y,FU M,LU X Q.Substance Dependence Constrained Sparse NMF for Hyperspectral Unmixing[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(6):2975-2986. [11]ADAMS J B,SABOL D E,KAPOS V,et al.Classification of multispectral images based on fractions of endmembers:Application to land-cover change in the Brazilian Amazon[J].Remote Sensing of Environment,1995,52(2):137-154. [12]ADAMS J B,SMITH M O,JOHNSON P E.Spectral mixture modeling:of rock and soil types at the Viking Larder 1 site[J].Journal of Geophysical Research:Solid Earth(1978-2012),1986,91(8):8098-8112. [13]DIAS J B,PLAZA A.Hyperspectral unmixing geometrical,statistical and sparse regression-based approaches[C]∥Procee-dings of SPIE:Image and Signal Processing for Remote Sensing XVI.Toulouse,France:SPIE Press,2010. [14]ZHAO C H,CHENG B Z,YANG W C.A hyperspectral unmi-xing algorithm based on the constraint nonnegative matrix decomposition[J].Journal of Harbin Institute of Technology,2012,33(3):378-382.(in Chinese) 赵春晖,成宝芝,杨伟超.利用约束非负矩阵分解的高光谱解混算法.哈尔滨工业大学学报,2012,33(3):378-382. [15]SONG Y G,WU Z B,WEI Z H,et al.Survey of sparsity constrained hyperspectral unmixing.Journal of Nanjing University of Science and Technoloogy,2013,37(4):486-492.(in Chinese) 宋义刚,吴泽彬,韦志辉,等.稀疏性高光谱解混方法研究[J].南京理工大学学报,2013,37(4):486-492. [16]KONG F J,BIAN C D,LI Y S,et al.Hyperspectral unmixing method for non-convex and low rank constraints[J].Journal of Xi’an Electronic and Science University(Natural Science Edition),2016,43(6):116-121.(in Chinese) 孔繁锵,卞陈鼎,李云松,等.非凸稀疏低秩约束的高光谱解混方法.西安电子科技大学学报(自然科学版),2016,43(6):116-121. [17]WANG T C,LIU X Z,DONG Z Z,et al.An adaptive robust minimum volume hyperspectral unmixing algorithm[J].Journal of Automation,2017,43(2):1-19.(in Chinese) 王天成,刘相振,董泽政,等.一种自适应鲁棒最小体积高光谱解混算法[J].自动化学报,2017,43(2):1-19. [18]LIU H,WU Z,CAI D,et al.Constrained non-negative matrix factorization for image representation[J].IEEE Transactions Pattern Analysis and Machine Intelligence,2012,34(7):1299-1311. [19]SHU Z Q,ZHAO C X.Constrained nonnegative matrix decomposition algorithm based on graph regularization and its application in image representation[J].Pattern Recognition and Artificial Intelligence,2013,26(3):300-306.(in Chinese) 舒振球,赵春霞.基于图正则化的受限非负矩阵分解算法及其在图像表示中的应用[J].模式识别与人工智能,2013,26(3):300-306. [20]PLAZA A,MARTINEZ P,PEREZ R,et al.A quantitative and comparative analysis of endmember extraction algorithms from hyperspectral data[J].IEEE Geoscience and Remote Sensing Letters,2004,42(3):650-663. [21]KESHAVA N,MUSTARD J F.Spectral unmixing[J].IEEESignal Process Mag,2002,19(1):44-57. [22]LANDGREBE D.Multispectral data analysis:a signal theoryperspective[D].West Lafayette:Purdye University,1998. [23]SWAYZE G.The hydrothermal l and structural history of the cuprite mining district,southwestern Nevada:an integrated geological and geophysical approach[D].Boulde:University of Co-lorado,1997. |
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