A band selection approach for small target detection based on CEM
暂无分享,去创建一个
[1] Felix Hueber,et al. Hyperspectral Imaging Techniques For Spectral Detection And Classification , 2016 .
[2] M. Ahmad,et al. A New Statistical Approach for Band Clustering and Band Selection Using K-Means Clustering , 2022 .
[3] Lorenzo Bruzzone,et al. A technique for feature selection in multiclass problems , 2000 .
[4] 赵永超,et al. A Gaussian elimination based fast endmember extraction algorithm for hyperspectral imagery , 2013 .
[5] O. L. Frost,et al. An algorithm for linearly constrained adaptive array processing , 1972 .
[6] B. Mojaradia,et al. A NOVEL BAND SELECTION METHOD FOR HYPERSPECTRAL DATA ANALYSIS , 2008 .
[7] Louis L. Scharf,et al. The CFAR adaptive subspace detector is a scale-invariant GLRT , 1999, IEEE Trans. Signal Process..
[8] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[9] Chein-I Chang,et al. Constrained band selection for hyperspectral imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[10] C. A. Murthy,et al. Unsupervised Feature Selection Using Feature Similarity , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[11] P. Switzer,et al. A transformation for ordering multispectral data in terms of image quality with implications for noise removal , 1988 .
[12] LinLin Shen,et al. Unsupervised Band Selection for Hyperspectral Imagery Classification Without Manual Band Removal , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[13] Ottawa Kia Oy. On Statistical Band Selection for Image Visualization , 2001 .
[14] Chein-I Chang,et al. Estimation of number of spectrally distinct signal sources in hyperspectral imagery , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[15] Lorenzo Bruzzone,et al. An extension of the Jeffreys-Matusita distance to multiclass cases for feature selection , 1995, IEEE Trans. Geosci. Remote. Sens..
[16] Qian Du,et al. Similarity-Based Unsupervised Band Selection for Hyperspectral Image Analysis , 2008, IEEE Geoscience and Remote Sensing Letters.
[17] Qian Du,et al. A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification , 1999, IEEE Trans. Geosci. Remote. Sens..
[18] Bor-Chen Kuo,et al. A Kernel-Based Feature Selection Method for SVM With RBF Kernel for Hyperspectral Image Classification , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[19] P. Chavez,et al. STATISTICAL METHOD FOR SELECTING LANDSAT MSS RATIOS , 1982 .
[20] Qian Du,et al. An Efficient Method for Supervised Hyperspectral Band Selection , 2011, IEEE Geoscience and Remote Sensing Letters.
[21] Adolfo Martínez Usó,et al. Clustering-Based Hyperspectral Band Selection Using Information Measures , 2007, IEEE Transactions on Geoscience and Remote Sensing.
[22] Yongchao Zhao,et al. CEM: More Bands, Better Performance , 2014, IEEE Geoscience and Remote Sensing Letters.
[23] Marco Diani,et al. Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection , 2013 .
[24] Mingyi He,et al. Band selection based on feature weighting for classification of hyperspectral data , 2005, IEEE Geoscience and Remote Sensing Letters.
[25] N. Keshava,et al. Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[26] Ye Zhang,et al. A Novel Geometry-Based Feature-Selection Technique for Hyperspectral Imagery , 2007, IEEE Geoscience and Remote Sensing Letters.
[27] Gary A. Shaw,et al. Hyperspectral subpixel target detection using the linear mixing model , 2001, IEEE Trans. Geosci. Remote. Sens..
[28] José M. Bioucas-Dias,et al. Hyperspectral Subspace Identification , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[29] Seungjin Choi,et al. Independent Component Analysis , 2009, Handbook of Natural Computing.
[30] Chein-I Chang,et al. A fast two-stage classification method for high-dimensional remote sensing data , 1998, IEEE Trans. Geosci. Remote. Sens..
[31] Yongchao Zhao,et al. A Fast Endmember Extraction Algorithm Based on Gram Determinant , 2014, IEEE Geoscience and Remote Sensing Letters.
[32] Thomas Marill,et al. On the effectiveness of receptors in recognition systems , 1963, IEEE Trans. Inf. Theory.
[33] Chein-I Chang,et al. Variable-Number Variable-Band Selection for Feature Characterization in Hyperspectral Signatures , 2007, IEEE Transactions on Geoscience and Remote Sensing.