Edge-preserving-based collaborative representation for spectral-spatial classification

References

• Bao, R., J. Xia, M. Dalla Mura, P. Du, J. Chanussot, and J. Ren. 2016. “Combining Morphological Attribute Profiles via an Ensemble Method for Hyperspectral Image Classification.” IEEE Geoscience Remote Sensing Letters 13: 359–363.
   Web of Science ®Google Scholar
• Benediktsson, J., J. Aevar Palmason, and J. R. Sveinsson. 2005. “Classification of Hyperspectral Data from Urban Areas Based on Extended Morphological Profiles.” IEEE Transactions on Geoscience and Remote Sensing 43 (3): 480–491. doi:10.1109/TGRS.2004.842478.
   Web of Science ®Google Scholar
• Berge, A., and A. H. S. Solberg. 2006. “Structured Gaussian Components for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 44: 3386–3396. doi:10.1109/TGRS.2006.880626.
   Web of Science ®Google Scholar
• Bruzzone, L., and M. Marconcini. 2009. “Toward the Automatic Updating of Land-Cover Maps by a Domain-Adaptation SVM Classifier and a Circular Validation Strategy.” IEEE Transactions on Geoscience and Remote Sensing 47: 1108–1122. doi:10.1109/TGRS.2008.2007741.
   Web of Science ®Google Scholar
• Camps-Valls, G., and L. Bruzzone. 2005. “Kernel-Based Methods for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 43: 1351–1362. doi:10.1109/TGRS.2005.846154.
   Web of Science ®Google Scholar
• Camps-Valls, G., L. Gómez-Chova, J. Calpe, E. Soria, J. D. Martín, L. Alonso, and J. Moreno. 2004. “Robust Support Vector Method for Hyperspectral Data Classification and Knowledge Discovery.” IEEE Transactions on Geoscience and Remote Sensing 42: 1530–1542. doi:10.1109/TGRS.2004.827262.
   Web of Science ®Google Scholar
• Camps-Valls, G., L. Gomez-Chova, J. Muéz-Mari, J. Vila-Frances, and J. Calpe-Maravilla. 2006. “Composite Kernels for Hyperspectral Image Classification.” IEEE Geoscience and Remote Sensing Letters 3: 93–97. doi:10.1109/LGRS.2005.857031.
   Web of Science ®Google Scholar
• Chang, C., and C. Linin, 2008. LIBSVM—A Library for Support Vector Machines. Accessed May 9, 2001. http://www.csie.ntu.edu.tw/~cjlin/libsvm.
   Google Scholar
• Cheng, Y. 1995. “Mean Shift, Mode Seeking, and Clustering.” IEEE Transactions on Pattern Analysis and Machine Intelligence 17: 790–799. doi:10.1109/34.400568.
   Web of Science ®Google Scholar
• Cohen, J. 1960. “A Coefficient of Agreement from Nominal Scales.” Educational and Psychological Measurement 20: 37–46. doi:10.1177/001316446002000104.
   Web of Science ®Google Scholar
• Dalla Mura, M., J. A. Benediktsson, B. Waske, and L. Bruzzone. 2010. “Extended Profiles with Morphological Attribute Filters for the Analysis of Hyperspectral Data.” International Journal of Remote Sensing 31 (22): 5975–5991. doi:10.1080/01431161.2010.512425.
   Web of Science ®Google Scholar
• Duda, R. O., P. E. Hart, and D. G. Stork. 2001. Pattern Classification. 2nd ed. New York, NY, USA: Wiley.
   Google Scholar
• Foody, G. M. 2004. “Thematic Map Comparison: Evaluating the Statistical Significance of Differences in Classification Accuracy.” Photogrammetric Engineering & Remote Sensing 70: 627–633. doi:10.14358/PERS.70.5.627.
   Web of Science ®Google Scholar
• Golipour, M., H. Ghassemian, and F. Mirzapour. 2016. “Integrating Hierarchical Segmentation Maps with MRF Prior for Classification of Hyperspectral Images in a Bayesian Framework.” IEEE Transactions on Geoscience and Remote Sensing 54: 805–816. doi:10.1109/TGRS.2015.2466657.
   Web of Science ®Google Scholar
• Gu, Y., C. Wang, D. You, Y. Zhang, S. Wang, and Y. Zhang. 2012. “Representative Multiple Kernel Learning for Classification in Hyperspectral Imagery.” IEEE Transactions on Geoscience and Remote Sensing 50: 2852–2865. doi:10.1109/TGRS.2011.2176341.
   Web of Science ®Google Scholar
• Gu, Y., T. Liu, X. Jia, J. A. Benediktsson, and J. Chanussot. 2016. “Nonlinear Multiple Kernel Learning with Multiple-Structure-Element Extended Morphological Profiles for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 54: 3235–3247. doi:10.1109/TGRS.2015.2514161.
   Web of Science ®Google Scholar
• Gualtieri, J. A., and R. F. Cromp. 1998. “Support Vector Machines for Hyperspectral Remote Sensing Classification.” Proceedings SPIE Workshop Advancement Computation Assisted Recog 3584: 221–232.
   Google Scholar
• Hosseini, S. A., and H. Ghassemian. 2015. “Rational Function Approximation for Feature Reduction in Hyperspectral Data.” Remote Sensing Letters 7: 101–110. doi:10.1080/2150704X.2015.1101180.
   Web of Science ®Google Scholar
• Imani, M., and H. Ghassemian. 2015. “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. 2016. “Binary Coding Based Feature Extraction in Remote Sensing High Dimensional Data.” Information Sciences 342: 191–208. doi:10.1016/j.ins.2016.01.032.
   Web of Science ®Google Scholar
• Jia, S., G. Tang, J. Zhu, and Q. Li. 2016. “A Novel Ranking-Based Clustering Approach for Hyperspectral Band Selection.” IEEE Transactions on Geoscience and Remote Sensing 54: 88–102. doi:10.1109/TGRS.2015.2450759.
   Web of Science ®Google Scholar
• Jin, X., and Y. Gu. 2017. “Superpixel-Based Intrinsic Image Decomposition of Hyperspectral Images.” IEEE Transactions on Geoscience and Remote Sensing 1–11. doi:10.1109/TGRS.2017.2690445.
   Web of Science ®Google Scholar
• Kang, X., S. Li, and J. Benediktsson. 2014a. “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., S. Li, and J. A. Benediktsson. 2014b. “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., S. Li, 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
• Kianisarkaleh, A., and H. Ghassemian. 2016. “Nonparametric Feature Extraction for Classification of Hyperspectral Images with Limited Training Samples.” ISPRS Journal of Photogrammetry and Remote Sensing 119: 64–78. doi:10.1016/j.isprsjprs.2016.05.009.
   Web of Science ®Google Scholar
• Kowkabi, F., H. Ghassemian, and A. Keshavarz. 2016. “Enhancing Hyperspectral Endmember Extraction Using Clustering and Oversegmentation-Based Preprocessing.” IEEE Journal Selected Topics in Applied Earth Observations and Remote Sensing 9 (6).
   PubMed Web of Science ®Google Scholar
• Li, J., P. Marpu, A. Plaza, J. Bioucas-Dias, and J. A. Benediktsson. 2013. “Generalized Composite Kernel Framework for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 51: 4816–4829. doi:10.1109/TGRS.2012.2230268.
   Web of Science ®Google Scholar
• Li, J., X. Huang, P. Gamba, J. M. Bioucas-Dias, L. Zhang, J. Benediktsson, and A. Plaza. 2015. “Multiple Feature Learning for Hyperspectral Image Classification.” IEEE Transactions on Geoscience and Remote Sensing 53 (3): 1592–1606. doi:10.1109/TGRS.2014.2345739.
   Web of Science ®Google Scholar
• Li, W., E. W. Tramel, S. Prasad, and J. E. Fowler. 2014. “Nearest Regularized Subspace for Hyperspectral Classification.” IEEE Transactions on Geoscience and Remote Sensing 52: 477–489. doi:10.1109/TGRS.2013.2241773.
   Web of Science ®Google Scholar
• Li, W., and Q. Du. 2014. “Joint Within-Class Collaborative Representation for Hyperspectral Image Classification.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7: 2200–2208. doi:10.1109/JSTARS.2014.2306956.
   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.” IEEE Signalling Processing Magazine 31: 55–66. doi:10.1109/MSP.2013.2279894.
   Web of Science ®Google Scholar
• Pesaresi, M., and J. A. Benediktsson. 2001. “A New Approach for the Morphological Segmentation of High-resolution Satellite Imagery.” IEEE Transactions on Geoscience and Remote Sensing 39 (2): 309–320.
   Web of Science ®Google Scholar
• Tarabalka, Y., J. A. Benediktsson, and J. Chanussot. 2009. “Spectral–Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques.” IEEE Transactions on Geoscience and Remote Sensing 47: 2973–2987. doi:10.1109/TGRS.2009.2016214.
   Web of Science ®Google Scholar
• Tilton, J. C., Y. Tarabalka, P. M. Montesano, and E. Gofman. 2012. “Best Merge Region-Growing Segmentation with Integrated Nonadjacent Region Object Aggregation.” IEEE Transactions on Geoscience and Remote Sensing 50: 4454–4467. doi:10.1109/TGRS.2012.2190079.
   Web of Science ®Google Scholar
• Wang, L., S. Hao, Q. Wang, and Y. Wang. 2014. “Semi-Supervised Classification for Hyperspectral Imagery Based on Spatial-Spectral Label Propagation, ISPRS J.” ISPRS Journal of Photogrammetry and Remote Sensing 97: 123–137. doi:10.1016/j.isprsjprs.2014.08.016.
   Web of Science ®Google Scholar
• Xia, J., L. Bombrun, T. Adalı, Y. Berthoumieu, and C. Germain. 2016. “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
• Xiong, M., Q. Ran, W. Li, J. Zou, and Q. Du. 2015. “Hyperspectral Image Classification Using Weighted Joint Collaborative Representation.” IEEE Geoscience and Remote Sensing Letters 12: 1209–1213. doi:10.1109/LGRS.2015.2388703.
   Web of Science ®Google Scholar
• Zehtabian, A., and H. Ghassemian. 2015. “An Adaptive Pixon Extraction Technique for Multispectral/Hyperspectral Image Classification.” IEEE Geoscience and Remote Sensing Letters 12: 831–835. doi:10.1109/LGRS.2014.2363586.
   Web of Science ®Google Scholar