A new hybrid feature extraction method in a dyadic scheme for classification of hyperspectral data

References

• Bandos, T. V., L. Bruzzone, and G. Camps-Valls. 2009. “Classification of Hyperspectral Images with Regularized Linear Discriminant Analysis.” IEEE Transactions on Geoscience and Remote Sensing 47 (Mar): 3.
   Web of Science ®Google Scholar
• Baudat, G., and F. Anouar. 2000. “Generalized Discriminant Analysis Using a Kernel Approach.” Neural Computation 12: 2385–2404. doi:10.1162/089976600300014980.
   PubMed Web of Science ®Google Scholar
• Bradley, P. S., and U. M. Fayyad. 1998. “Refining Initial Points for K-Means Clustering.” In ICML 98: 91–99.
   Google Scholar
• Chang, C., and C. Linin, 2008. “LIBSVM—A Library for Support Vector Machines.” Accessed 15 February 2016. http://www.csie.ntu.edu.tw/~cjlin/libsvm.
   Google Scholar
• Chang, Y.-L., J.-N. Liu, -C.-C. Han, and Y.-N. Chen. 2014. “Hyperspectral Image Classification Using Nearest Feature Line Embedding Approach.” IEEE Transactions on Geoscience and Remote Sensing 52: 278–287. doi:10.1109/TGRS.2013.2238635.
   Web of Science ®Google Scholar
• Cohen, J. 1960. “A Coefficient of Agreement from Nominal Scales.” Education Psychologist Measuring 20: 37–46. doi:10.1177/001316446002000104.
   Web of Science ®Google Scholar
• Cui, Y., and L. Fan. 2012. “Feature Extraction Using Fuzzy Maximum Margin Criterion.” Neurocomputing 86: 52–58. doi:10.1016/j.neucom.2011.12.031.
   Web of Science ®Google Scholar
• Demarchi, L., F. Canters, C. Cariou, G. Licciardi, and J. Cheung-Wai Chan. 2014. “Assessing the Performance of Two Unsupervised Dimensionality Reduction Techniques on Hyperspectral APEX Data for High Resolution Urban Land-Cover Mapping.” ISPRS Journal of Photogrammetry and Remote Sensing 87: 166–179. doi:10.1016/j.isprsjprs.2013.10.012.
   Web of Science ®Google Scholar
• Dhanjal, C., S. R. Gunn, and J. Shawe-Taylor. 2009. “Efficient Sparse Kernel Feature Extraction Based on Partial Least Squares.” IEEE Transactions Pattern Analysis Mach Intelligent 31: 1347–1361. doi:10.1109/TPAMI.2008.171.
   PubMed Web of Science ®Google Scholar
• Feng, J., L. Jiao, T. Sun,  H. Liu, and  X. Zhang. 2016. “Multiple Kernel Learning Based on Discriminative Kernel Clustering for Hyperspectral Band Selection.” IEEE Transactions on Geoscience and Remote Sensing 54 (11): 6516–6530. doi:10.1109/TGRS.2016.2585961.
   Web of Science ®Google Scholar
• Ghassemian, H., and D. A. Landgrebe. 1988. “Object-Oriented Feature Extraction Method for Image Data Compaction.” IEEE Control Systems Magazine 8: 42–48. doi:10.1109/37.476.
   Google Scholar
• Green, A. A., M. Berman, P. Switzer, and M. D. Craig. 1988. “A Transformation for Ordering Multispectral Data in Terms of Image Quality with Implications for Noise Removal.” IEEE Transactions on Geoscience and Remote Sensing 26: 65–74. doi:10.1109/36.3001.
   Web of Science ®Google Scholar
• Hsu, P.-H. 2007. “Feature Extraction of Hyperspectral Images Using Wavelet and Matching Pursuit.” ISPRS Journal of Photogrammetry and Remote Sensing 62: 78–92. doi:10.1016/j.isprsjprs.2006.12.004.
   Web of Science ®Google Scholar
• Huang, Z. H., W. J. Li, J. Wang, and T. Zhang. 2015. “Face Recognition Based on Pixel-Level and Feature-Level Fusion of the Top-Level’s Wavelet Sub-Bands.” Information Fusion 22: 95–104. doi:10.1016/j.inffus.2014.06.001.
   Web of Science ®Google Scholar
• Hughes, G. F. 1968. “On the Mean Accuracy of Statistical Pattern Recognition.” IEEE Transactions Informatics Theory IT 14: 55–63. doi:10.1109/TIT.1968.1054102.
   Web of Science ®Google Scholar
• Imani, M., and H. Ghassemian. 2014a. “Band Clustering-Based Feature Extraction for Classification of Hyperspectral Images Using Limited Training Samples.” IEEE Geoscience and Remote Sensing Letters 11: 1325–1329. doi:10.1109/LGRS.2013.2292892.
   Web of Science ®Google Scholar
• Imani, M., and H. Ghassemian. 2014b. “Feature Extraction Using Attraction Points for Classification of Hyperspectral Images in Small Sample Size Situation.” IEEE Geoscience and Remote Sensing Letters 11: 1986–1990.
   Web of Science ®Google Scholar
• Imani, M., and H. Ghassemian. 2015a. “Feature Space Discriminant Analysis for Hyperspectral Data Feature Reduction.” ISPRS Journal of Photogrammetry and Remote Sensing 102: 1–13. doi:10.1016/j.isprsjprs.2014.12.024.
   Web of Science ®Google Scholar
• Imani, M., and H. Ghassemian. 2015b. “Ridge Regression-Based Feature Extraction for Hyperspectral Data.” International Journal of Remote Sensing 36 (6): 1728–1742. doi:10.1080/01431161.2015.1024894.
   Web of Science ®Google Scholar
• Jiao, L. C., F. Shang, F. Wang, and Y. Liu. 2012. “Fast Semi-Supervised Clustering with Enhanced Spectral Embedding.” Pattern Recognition 45 (12): 4358–4369. doi:10.1016/j.patcog.2012.05.007.
   Web of Science ®Google Scholar
• Kamandar, M., and H. Ghassemian. 2013. “Linear Feature Extraction for Hyperspectral Images Based on Information Theoretic Learning.” IEEE Geoscience and Remote Sensing Letters 10: 702–706. doi:10.1109/LGRS.2012.2219575.
   Web of Science ®Google Scholar
• Karakatič, S., and V. Podgorelec. 2016. “Improved Classification with Allocation Method and Multiple Classifiers.” Information Fusion 31: 26–42. doi:10.1016/j.inffus.2015.12.006.
   Web of Science ®Google Scholar
• Kuo, B. C., and D. A. Landgrebe. 2004. “Nonparametric Weighted Feature Extraction for Classification.” IEEE Transactions on Geoscience and Remote Sensing 42: 1096–1105. doi:10.1109/TGRS.2004.825578.
   Web of Science ®Google Scholar
• Kuo, B.-C., C.-H. Li, and J.-M. Yang. 2009. “Kernel Nonparametric Weighted Feature Extraction for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 47: 1139–1155. doi:10.1109/TGRS.2008.2008308.
   Web of Science ®Google Scholar
• Law, M. H., and A. K. Jain. 2006. “Incremental Nonlinear Dimensionality Reduction by Manifold Learning.” IEEE Transactions on Pattern Analysis and Machine Intelligence 28 (3): 377–391. doi:10.1109/TPAMI.2006.56.
   PubMed Web of Science ®Google Scholar
• Li, F., L. Xu, A. Wong, and D. A. Clausi. 2015. “Feature Extraction for Hyperspectral Imagery via Ensemble Localized Manifold Learning.” IEEE Geoscience and Remote Sensing Letters 12 (12): 2486–2490. doi:10.1109/LGRS.2015.2487226.
   Web of Science ®Google Scholar
• Li, W., J. Liu, and Q. Du. 2016. “Sparse and Low-Rank Graph for Discriminant Analysis of Hyperspectral Imagery.” IEEE Transactions on Geoscience and Remote Sensing 54 (7): 4094–4105. doi:10.1109/TGRS.2016.2536685.
   Web of Science ®Google Scholar
• Liao, W., R. Bellens, A. Pizˇurica, W. Philips, and Y. Pi. 2012. “Classification of Hyperspectral Data over Urban Areas Using Directional Morphological Profiles and Semi-Supervised Feature Extraction.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5: 1177–1190. doi:10.1109/JSTARS.2012.2190045.
   Web of Science ®Google Scholar
• Löw, F., U. Michel, S. Dech, and C. Conrad. 2013. “Impact of feature selection on the accuracy and Spatial Uncertainty of Per-Field Crop Classification Using Support Vector Machines.” ISPRS Journal of Photogrammetry and Remote Sensing 85: 102–119. doi:10.1016/j.isprsjprs.2013.08.007.
   Web of Science ®Google Scholar
• Lunga, D., S. Prasad, M. M. Crawford, and O. Ersoy. 2014. “Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning.” IEEE Signal Processing Magazine 31 (1): 55–66. doi:10.1109/MSP.2013.2279894.
   Web of Science ®Google Scholar
• Martínez, A. M., and A. C. Kak. 2001. “PCA versus LDA.” IEEE Transactions Pattern Analysis Mach Intelligent 23: 228–233. doi:10.1109/34.908974.
   Web of Science ®Google Scholar
• Mirzapour, F., and H. Ghassemian. 2015. “Improving Hyperspectral Image Classification by Combining Spectral, Texture, and Shape Features.” International Journal Remote Sensing 36 (4): 1070–1096.
   Web of Science ®Google Scholar
• Nielsen, A. A. 2011. “Kernel Maximum Autocorrelation Factor and Minimum Noise Fraction Transformations.” IEEE Transactions Image Processing 20: 612–624. doi:10.1109/TIP.2010.2076296.
   PubMed Web of Science ®Google Scholar
• Okada, T., and S. Tomita. 1985. “An Optimal Orthonormal System for Discriminant Analysis.” Pattern Recognition 18: 139–144. doi:10.1016/0031-3203(85)90037-8.
   Web of Science ®Google Scholar
• Plaza, A. 2005. “Pablo Martínez, Javier Plaza, and Rosa Pérez Dimensionality Reduction and Classification of Hyperspectral Image Data Using Sequences of Extended Morphological Transformations.” IEEE Transactions on Geoscience and Remote Sensing 43 (Mar): 3. doi:10.1109/TGRS.2004.841417.
   Web of Science ®Google Scholar
• Schölkopf, B., A. Smola, and K.-R. Müller. 1998. “Nonlinear Component Analysis as a Kernel Eigenvalue Problem.” Neural Computation 10: 1299–1319. doi:10.1162/089976698300017467.
   Web of Science ®Google Scholar
• Shahdoosti, H. R., and N. Javaheri. 2017. “Pansharpening of Clustered MS and Pan Images considering Mixed Pixels.” IEEE Geoscience and Remote Sensing Letters 14 (6): 826–830. doi:10.1109/LGRS.2017.2682122.
   Web of Science ®Google Scholar
• Shahdoosti, H. R., and F. Mirzapour. 2017. “Spectral–Spatial Feature Extraction Using Orthogonal Linear Discriminant Analysis for Classification of Hyperspectral Data.” European Journal of Remote Sensing 50 (1): 111–124. doi:10.1080/22797254.2017.1279821.
   Web of Science ®Google Scholar
• Shang, R., Z. Zhang,  L. Jiao,  W. Wang, and  S. Yang. 2016a. “Global Discriminative-Based Nonnegative Spectral Clustering”. Pattern Recognition 55: 172–182. doi:10.1016/j.patcog.2016.01.035.
   Web of Science ®Google Scholar
• Shang, R., Z. Zhang, L. Jiao, C. Liu, and Y. Li. 2016b. “Self-Representation Based Dual-Graph Regularized Feature Selection Clustering.” Neurocomputing 171: 1242–1253. doi:10.1016/j.neucom.2015.07.068.
   Web of Science ®Google Scholar
• Switzer, P., and A. A. Green, 1984. “Min/Max Autocorrelation Factors for Multivariate Spatial Imagery.” Technical Report No 6. Department of Computer science and statistics, Stanford University.
   Google Scholar
• Universidad-del-País-Vasco. 2014. “Hyperspectral Remote Sensing Scenes.” Accessed 15 January 2016. http://www.ehu.es/ccwintco/index.php?title=Hyperspectral_Remote_Sensing_Scenes.
   Google Scholar
• Ye, J., and T. Xiong. 2006. “Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis.” Journal Mach Learning Researcher 7 (Jul): 1183–1204.
   Web of Science ®Google Scholar
• Yin, J., C. Gao, and X. Jia. 2013. “Wavelet Packet Analysis and Gray Model for Feature Extraction of Hyperspectral Data.” IEEE Geoscience and Remote Sensing Letters 10: 682–686. doi:10.1109/LGRS.2012.2218569.
   Web of Science ®Google Scholar
• Yin, J., Y. Wang, and J. Hu. 2012. “A New Dimensionality Reduction Algorithm for Hyperspectral Image Data Using Evolutionary Strategy.” IEEE Transactions Informatics Theory 8: 935–943. doi:10.1109/TII.2012.2205397.
   Web of Science ®Google Scholar
• Zabalza, J., J. Ren, Z. Wang, S. Marshall, and J. Wang. 2014. “Singular Spectrum Analysis for Effective Feature Extraction in Hyperspectral Imaging.” IEEE Geoscience and Remote Sensing Letters 11 (11): 1886–1890. doi:10.1109/LGRS.2014.2312754.
   Web of Science ®Google Scholar
• Zabalza, J., J. Ren, M. Yang, Y. Zhang, J. Wang, S. Marshall, and J. Han. 2014. “Novel folded-PCA for Improved Feature Extraction and Data Reduction with Hyperspectral Imaging and SAR in Remote Sensing.” ISPRS Journal of Photogrammetry and Remote Sensing 93: 112–122. doi:10.1016/j.isprsjprs.2014.04.006.
   Web of Science ®Google Scholar
• Zabalza, J., J. Ren, J. Zheng, J. Han, H. Zhao, S. Li, and S. Marshall. 2015. “Novel Two-Dimensional Singular Spectrum Analysis for Effective Feature Extraction and Data Classification in Hyperspectral Imaging.” IEEE Transactions on Geoscience and Remote Sensing 53 (8): 4418–4433. doi:10.1109/TGRS.2015.2398468.
   Web of Science ®Google Scholar
• Zhang, L., L. Zhang, D. Tao, and X. Huang. 2012. “On Combining Multiple Features for Hyperspectral Remote Sensing Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 50 (3): 879–893. doi:10.1109/TGRS.2011.2162339.
   Web of Science ®Google Scholar
• Zhang, L., L. Zhang, D. Tao, and X. Huang. 2013. “Tensor Discriminative Locality Alignment for Hyperspectral Image Spectral–Spatial Feature Extraction.” IEEE Transactions on Geoscience and Remote Sensing 51: 242–256. doi:10.1109/TGRS.2012.2197860.
   Web of Science ®Google Scholar
• Zhang, L., Q. Zhang, L. Zhang, D. Tao, X. Huang, and B. Du. 2015. “Ensemble Manifold Regularized Sparse Low-Rank Approximation for Multiview Feature Embedding.” Pattern Recognition 48 (10): 3102–3112. doi:10.1016/j.patcog.2014.12.016.
   Web of Science ®Google Scholar