Longwave infrared hyperspectral image classification via an ensemble method

References

• Barisione, F., D. Solarna, A. De Giorgi, G. Moser, and S. B. Serpico. 2016. “Supervised Classification of Thermal Infrared Hyperspectral Images through Bayesian, Markovian, and Region-Based Approaches.” In Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International, 937–940. IEEE.
   Google Scholar
• Chi, M., K. Qian, J. A. Benediktsson, and R. Feng. 2009. “Ensemble Classification Algorithm for Hyperspectral Remote Sensing Data.” IEEE Geoscience and Remote Sensing Letters 6 (4): 762–766. doi:10.1109/LGRS.2009.2024624.
   Web of Science ®Google Scholar
• Cubero-Castan, M., J. Chanussot, V. Achard, X. Briottet, and M. Shimoni. 2015. “A Physics-Based Unmixing Method to Estimate Subpixel Temperatures on Mixed Pixels.” IEEE Transactions on Geoscience and Remote Sensing 53 (4): 1894–1906. doi:10.1109/TGRS.2014.2350771.
   Web of Science ®Google Scholar
• Dietterich, T. G. 2000. “Ensemble Methods in Machine Learning.” In International Workshop on Multiple Classifier Systems, 1–15.
   Google Scholar
• Foody, G. M. 2004. “Thematic Map Comparison: Evaluating the Statistical Significance of Differences in Classification Accuracy.” Photogrammetric Engineering and Remote Sensing 70 (5): 627–633. doi:10.14358/PERS.70.5.627.
   Web of Science ®Google Scholar
• GRSS Data Fusion Contest. 2014. Image Analysis and Data Fusion. IEEE. Online: http://www.grss-ieee.org/community/technical-committees/data-fusion/.
   Google Scholar
• Gu, Y., T. Liu, X. Jia, and J. A. Benediktsson. 2016. “Nonlinear Multiple Kernel Learning with Multiple-Structure-Element Extended Morphological Profiles for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 54 (6): 3235–3247. doi:10.1109/TGRS.2015.2514161.
   Web of Science ®Google Scholar
• Han, X., Y. Zhong, B. Zhao, and L. Zhang. 2017. “Scene Classification Based on a Hierarchical Convolutional Sparse Auto-Encoder for High Spatial Resolution Imagery.” International Journal of Remote Sensing 38 (2): 514–536.
   Google Scholar
• Huang, X., and L. Zhang. 2013. “An SVM Ensemble Approach Combining Spectral, Structural, and Semantic Features for the Classification of High-Resolution Remotely Sensed Imagery.” IEEE Transactions on Geoscience and Remote Sensing 51 (1): 257–272. doi:10.1109/TGRS.2012.2202912.
   Web of Science ®Google Scholar
• Hunt, G. R. 1977. “Spectral Signatures of Particulate Minerals in the Visible and near Infrared.” Geophysics 42 (3): 501–513. doi:10.1190/1.1440721.
   Web of Science ®Google Scholar
• Jiao, H., Y. Zhong, and L. Zhang. 2014. “An Unsupervised Spectral Matching Classifier Based on Artificial DNA Computing for Hyperspectral Remote Sensing Imagery.” IEEE Transactions on Geoscience and Remote Sensing 52 (8): 4524–4538. doi:10.1109/TGRS.2013.2282356.
   Web of Science ®Google Scholar
• Jun, L., P. R. Marpu, A. Plaza, J. M. Bioucas-Dias, and J. A. Benediktsson. 2013. “Generalized Composite Kernel Framework for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 51 (9): 4816–4829. doi:10.1109/TGRS.2012.2230268.
   Web of Science ®Google Scholar
• Kang, X., L. Shutao, and J. A. Benediktsson. 2014. “A. “Feature Extraction of Hyperspectral Images with Image Fusion and Recursive Filtering.”.” IEEE Transactions on Geoscience and Remote Sensing 52 (6): 3742–3752. doi:10.1109/TGRS.2013.2275613.
   Web of Science ®Google Scholar
• Kang, X., L. Shutao, and J. A. Benediktsson. 2014b. “Spectral–Spatial Hyperspectral Image Classification with Edge-Preserving Filtering.” IEEE Transactions on Geoscience and Remote Sensing 52 (5): 2666–2677. doi:10.1109/TGRS.2013.2264508.
   Web of Science ®Google Scholar
• Kang, X., L. Shutao, L. Fang, and J. A. Benediktsson. 2015. “Intrinsic Image Decomposition for Feature Extraction of Hyperspectral Images.” IEEE Transactions on Geoscience and Remote Sensing 53 (4): 2241–2253. doi:10.1109/TGRS.2014.2358615.
   Web of Science ®Google Scholar
• Krogh, A., and J. Vedelsby. 1995. “Neural Network Ensembles, Cross Validation, And Active Learning.” Advances In Neural Information Processing Systems 7: 231–238.
   Google Scholar
• Li, W., and D. Qian. 2016. “A Survey on Representation-Based Classification and Detection in Hyperspectral Remote Sensing Imagery.” Pattern Recognition Letters 83: 115–123. doi:10.1016/j.patrec.2015.09.010.
   Web of Science ®Google Scholar
• Li, W., G. Wu, F. Zhang, and Q. Du. 2017. “Hyperspectral Image Classification Using Deep Pixel-Pair Features.” IEEE Transactions on Geoscience and Remote Sensing 55 (2): 844–853.
   Google Scholar
• Liao, W., X. Huang, F. Van Coillie, S. Gautama, A. Pižurica, W. Philips, H. Liu, et al. 2015. “Processing of Multiresolution Thermal Hyperspectral and Digital Color Data: Outcome of the 2014 IEEE GRSS Data Fusion Contest.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8 (6): 2984–2996. DOI:10.1109/JSTARS.2015.2420582.
   Web of Science ®Google Scholar
• Lucey, P. G., J. Julian, W. Schaff, E. M. Winter, A. D. Stocker, and A. P. Bowman. 1998. “AHI: An Airborne Long-Wave Infrared Hyperspectral Imager.” Proc Spie 3431: 36–43.
   Google Scholar
• Pal, M. 2008. “Ensemble of Support Vector Machines for Land Cover Classification.” International Journal of Remote Sensing 29 (10): 3043–3049. doi:10.1080/01431160802007624.
   Web of Science ®Google Scholar
• Pan, B., Z. Shi, N. Zhang, and S. Xie. 2016. “Hyperspectral Image Classification Based on Nonlinear Spectral-Spatial Network.” IEEE Geoscience and Remote Sensing Letters 13 (12): 1782–1786. doi:10.1109/LGRS.2016.2608963.
   Web of Science ®Google Scholar
• Pan, B., Z. Shi, and X. Xia. 2017a. “A Novel Spectral-Unmixing-Based Green Algae Area Estimation Method for GOCI Data.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10 (2): 437–449. doi:10.1109/JSTARS.2016.2585161.
   Web of Science ®Google Scholar
• Pan, B., Z. Shi, and X. Xia. 2017b. “R-VCANet: A New Deep Learning-Based Hyperspectral Image Classification Method.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10 (5): 1975–1986. doi:10.1109/JSTARS.2017.2655516.
   Web of Science ®Google Scholar
• Segl, K., S. Roessner, U. Heiden, and H. Kaufmann. 2003. “Fusion of Spectral and Shape Features for Identification of Urban Surface Cover Types Using Reflective and Thermal Hyperspectral Data.” ISPRS Journal of Photogrammetry and Remote Sensing 58 (1): 99–112. doi:10.1016/S0924-2716(03)00020-0.
   Web of Science ®Google Scholar
• Shimoni, M., and C. Perneel. 2012. “Dedicated Classification Method for Thermal Hyperspectral Imaging.” In 2012 IEEE International Geoscience and Remote Sensing Symposium, 1397–1400. IEEE.
   Google Scholar
• Xia, J., J. Chanussot, D. Peijun, and H. Xiyan. 2016b. “Rotation-Based Support Vector Machine Ensemble in Classification of Hyperspectral Data with Limited Training Samples.” IEEE Transactions on Geoscience and Remote Sensing 54 (3): 1519–1531. doi:10.1109/TGRS.2015.2481938.
   Web of Science ®Google Scholar
• Xia, J., L. Bombrun, T. Adal, Y. Berthoumieu, and C. Germain. 2016a. “Spectral–Spatial Classification of Hyperspectral Images Using ICA and Edge-Preserving Filter via an Ensemble Strategy.” IEEE Transactions on Geoscience and Remote Sensing 54 (8): 4971–4982. doi:10.1109/TGRS.2016.2553842.
   Web of Science ®Google Scholar
• Xu, X., and Z. Shi. 2017. “Multi-Objective Based Spectral Unmixing for Hyperspectral Images.” ISPRS Journal of Photogrammetry and Remote Sensing 124: 54–69. doi:10.1016/j.isprsjprs.2016.12.010.
   Web of Science ®Google Scholar
• Zhang, Q., X. Shen, X. Li, and J. Jia. 2014. “Rolling Guidance Filter.” In European Conference on Computer Vision (ECCV), 815–830. Springer.
   Google Scholar
• Zhong, Y., W. Yunyun, X. Xiong, and L. Zhang. 2015. “An Adaptive Subpixel Mapping Method Based on MAP Model and Class Determination Strategy for Hyperspectral Remote Sensing Imagery.” IEEE Transactions on Geoscience and Remote Sensing 53 (3): 1411–1426. doi:10.1109/TGRS.2014.2340734.
   Web of Science ®Google Scholar
• Zhou, Z. H. 2012. Ensemble Methods: Foundations and Algorithms. Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar