[3] Mehmet S, Buelent S. Survey over image thresholding techniques and quantitative performance evaluation \[J\]. Journal of Electronic Imaging, 2004, 13(1): 146-168.
[4] Bellon O R P, Silva L. New improvements to range image segmentation by edge detection \[J\]. IEEE Signal Processing Letters, 2002, 9(2): 43-45.
[7] Feng H, Hou B. SAR image despeckling based on local homogeneous-region segmentation by using pixel-relativity measurement \[J\]. IEEE Transactions on Geoscience & Remote Sensing, 2011, 49(7): 2724-2737.
[8] Chapel L, Burger T, Courty N, et al. PerTurbo manifold learning algorithm for weakly labeled hyperspectral image classification \[J\]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2014, 7(4): 1070-1078.
[9] Bruzzone L, Persello C. A novel context-sensitive semisupervised SVM classifier robust to mislabeled training samples \[J\]. IEEE Transactions on Geoscience & Remote Sensing, 2009, 47(7):2142-2154.
[10] Tan K, Zhou S, Du Q. Semisupervised discriminant analysis for hyperspectral imagery with block-sparse graph \[J\]. IEEE Geoscience& Remote Sensing Letters, 2015, 12(8): 1765-1769.
[11] Zhou Z H, Li M. Semi-supervised learning by disagreement \[J\]. Knowledge & Information Systems, 2010, 24(3): 415-439.
[12] Cui B, Xie X, Hao S, et al. Semi-supervised classification of hyperspectral images based on extended label propagation and rolling guidance filtering \[J\]. Remote Sensing, 2018, 10(4): 515.
[13] Amini S, Homayouni S, Safari A. Semi-supervised classification of hyperspectral image using random forest algorithm \[C\]. Quebec: IEEE Geoscience and Remote Sensing Symposium, 2014.
[15] Geng Y, Chen J, Wang L. A novel color image segmentation algorithm based on JSEG and Normalized Cuts \[C\]. Hangzhou: 6th International Congress on Image and Signal Processing, 2013.
[16] Achanta R, Shaji A, Smith K, et al. SLIC superpixels compared to state-of-the-art superpixel methods \[J\]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11): 2274-2282.
[19] Clinton N, Holt A, Scarborough J, et al. Accuracy assessment measures for object-based image segmentation goodness \[J\]. Photogrammetric Engineering & Remote Sensing, 2010, 76(3): 289-299.
[20] Li W, Wu G D, Zhang F. Hyperspectral image c Photogrammetric Engineering & Remote Sensing classification using deep pixel-pair features \[J\]. IEEE Transactions on Geoscience & Remote Sensing, 2017, 55(2): 844-853.
[21] Liu W, He J, Chang S F. Large graph construction for scalable semi-supervised learning \[C\]. Haifa: 27th International Conference on Machine Learning, 2010.