光学技术, 2018, 44 (5): 634, 网络出版: 2018-10-08   

基于高光谱基本准则的波段选择方法

Band selection method based on hyperspectral fundamental criterion
作者单位
陆军工程大学 石家庄校区电子与光学工程系, 河北 石家庄 050003
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严阳, 华文深, 刘恂, 崔子浩. 基于高光谱基本准则的波段选择方法[J]. 光学技术, 2018, 44(5): 634.

YAN Yang, HUA Wenshen, LIU Xun, CUI Zihao. Band selection method based on hyperspectral fundamental criterion[J]. Optical Technique, 2018, 44(5): 634.

参考文献

[1] Clark R N,Swayze G A. Imaging spectroscopy material maps: cuprite introduction[J/OL]. Summaries of the 6th Annual JPL Airborne Earth Science Workshop,1996.

[2] Kuo B, Landgrebe D. A covariance estimator for small size classification problem and its application to feature extraction [J]. IEEE Transactions on Geoscience and Remote Sensing,2002,40(4):814-819.

[3] Fan Li, Linlin XU, Alexander Wong, et al. Feature extraction for hyperspectral imagery via ensemble localized manifold learning[J]. Geoscience and Remote Sensing Letters, IEEE, 2015,12(12):2486-2490.

[4] Guokang Zhu, Yuancheng Huang, Jingsheng Lei, et al. Unsupervised hyperspectral band selection by dominant set extraction[J].IEEE Transactions on Geoscience and Remote Sensing, 2016,54(1):227-619.

[5] 陈扬, 张太宁, 郭澎, 等.基于主成分分析的复杂光谱定量分析方法的研究[J].光学学报, 2009, 29(5):1285-1291.

    Chen Yang, Zhang Taining, Guo Peng, et al. Quantitative analysis for nonlinear fluorescent spectra based on principal component analysis [J]. Acta Optica Sinica,2009,29(5):1285-1291.

[6] 张晶晶, 周晓勇, 刘奇.一种改进的大尺度高光谱流形降维算法[J].光学学报, 2013,33(11):1128001.

    Zhang Jingjing, Zhou Xiaoyong, Liu Qi. Improved dimensionality reduction algorithm of large-scale hyperspectral scenes using manifold[J].Acta Optica Sinica,2013,33(11):1128001.

[7] 丁小辉, 李华朋, 张树清.基于多态蚁群算法的高光谱遥感影像最优波段选择[J]. 遥感技术与应用, 2016,31(2):275-284.

    Ding Xiaohui, Li Huapeng, Zhang Shuqing. Optimized band selection of hyperspectral remote sensing image based on polymorphic ant colony algorithm[J]. Remote Sensing Technology and Application,2016,31(2):275-284.

[8] 任晓东, 雷武虎, 谷雨, 等.一种改进的高光谱图像波段选择方法[J].计算机科学, 2015, 42(11):162-168.

    Ren Xiaodong, Lei Wuhu, Gu Yu, et al. Improved band selection method for hyperspectral imagery[J]. Computer Science,2015,42(11):162-168.

[9] Serpico S, Moser G. Extraction of spectral channels from hyperspectral images for classification purposes[J].IEEE Transactions on Geoscience and Remote Sensing,2007,45(2):484-495.

[10] Marinez-Uso A, Pla F, Sotoca J, et al. Clustering-based hyperspectral band selection using information measures[J]. IEEE Transactions on Geoscience and Remote Sensing,2007,45(12):4158-4171.

[11] Archibald R, Fann G. Feature selection and classification of hyperspectral images with support vector machine[J].IEEE Transactions on Geoscience and Remote Sensing,2007,4(4):674-679.

[12] Pedram Ghamisi, Jon Atli Benediktsson, Magnus Orn Ulfarsson. Spectral-spatial classification of hyperspectral images based on hidden Markov Random Fields[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(5):2565-2574.

[13] 杨佳, 华文深, 刘恂, 等.基于K-L散度与光谱可分性距离的波段选择算法[J].应用光学,2014,35(1):71-75.

    Yang Jia, Hua Wenshen, Liu Xun, et al. Band selection algorithm for hyperspectral imagery based on K-L divergence and spectral divisibility distance[J]. Journal of Applied Optics,2014,35(1):71-75.

[14] Chang C I, Du Q. Estimation of number of spectrally distinct signal in hyperspectral imagery [J]. Geoscience and Remote Sensing, IEEE Transactions on,2004,42(3):608-619.

[15] 张海涛, 王鹤桥, 孟祥羽, 等.基于类对可分和灰色决策的高光谱波段选择[J].计算机科学,2014,41(6):309-313.

    Zhang Haitao, Wang Heqiao, Meng Xiangyu, et al. Hyperspectral band selection method based on conjugate class separability and grey decision[J]. Computer Science,2014,41(6):309-313.

[16] 秦方普, 张爱武, 王书民,等.基于谱聚类与类间可分性因子的高光谱波段选择[J]. 光谱学与光谱分析,2015,35(5):1357-1364.

    Qin Fangpu, Zhang Aiwu, Wang Shumin, et al. Hyperspectral band selection based on spectral clustering and inter-class separability factor[J]. Spectroscopy and Spectral,2015,35(5):1357-1364.

严阳, 华文深, 刘恂, 崔子浩. 基于高光谱基本准则的波段选择方法[J]. 光学技术, 2018, 44(5): 634. YAN Yang, HUA Wenshen, LIU Xun, CUI Zihao. Band selection method based on hyperspectral fundamental criterion[J]. Optical Technique, 2018, 44(5): 634.

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