Locality preserving fusion of multi-source images for sea-ice classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Aquatic Science,Oceanography
Link
http://link.springer.com/content/pdf/10.1007/s13131-019-1464-2.pdf
Reference19 articles.
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3. Huang Xin, Zhang Liangpen. 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: https://doi.org/10.1109/TGRS.2012.2202912
4. Kettig R L, Landgrebe D A. 1976. Classification of multispectral image data by extraction and classification of homogeneous objects. IEEE Transactions on Geoscience Electronics, 14(1): 19–26, doi: https://doi.org/10.1109/TGE.1976.294460
5. Liao Wenzhi, Pižurica A, Bellens R, et al. 2015. Generalized graph-based fusion of hyperspectral and LiDAR data using morphological features. IEEE Geoscience and Remote Sensing Letters, 12(3): 552–556, doi: https://doi.org/10.1109/LGRS.2014.2350263
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