Hierarchical clustering algorithms for segmentation of multispectral images

R. C. Gonzalez and R. E. Woods, Digital Image Processing (Tekhnosphera, Moscow, 2006) [in Russian].

P. A. Chochia, “Image Segmentation Based on the Analysis of Distances in an Attribute Space,” Avtometriya 50 (6), 97–110 (2014) [Optoelectron., Instrum. Data Process. 50 (6), 613–624 (2014)].

I. A. Pestunov and Yu. N. Sinyavskii, “Clustering Algorithms in Problems of Segmentation of Satellite Images,” Vestn. KemGU 2 (4(52)), 110–125 (2012).

R. Xu and D. I. Wunsch, “Survey of Clustering Algorithms,” IEEE Trans. Neural Networks 16 (3), 645–678 (2005).

A. K. Jain, “Data Clustering: 50 years Beyond K-Means,” Patt. Recogn. Lett. 31 (8), 651–666 (2010).

R. Ghaemi, M. Sulaiman, H. Ibrahim, and N. Mustapha, “A Survey: Clustering Ensembles Techniques,” World Acad. Sci., Eng. Technol. 3 (2), 535–544 (2009).

P. Hope, L. Hall, and D. Goldgof, “A Scalable Framework for Cluster Ensembles,” Patt. Recogn. 42 (5), 676–688 (2009).

R. Kashef and M. Kamel, “Cooperative Clustering,” Patt. Recogn. 43 (7), 2315–2329 (2010).

J. Jia, B. Liu, and L. Jiao, “Soft Spectral Clustering Ensemble Applied to Image Segmentation,” Front. Comput. Sci. China. 5 (1), 66–78 (2011).

L. Franek and X. Jiang, “Ensemble Clustering by Means of Clustering Embedding in Vectorspaces,” Patt. Recogn. 47 (2), 833–842 (2014).

A. Mirzaei and M. Rahmati, “A Novel Hierarchical-Clustering-Combination Scheme Based on Fuzzy-Similarity Relations,” IEEE Trans. Fuzzy Syst. 18 (1), 27–39 (2010).

L. Zheng, T. Li, and C. Ding, “Hierarchical Ensemble Clustering,” in Proc. of 2010 IEEE Intern. Conf. on Data Mining (IEEE, 2010), pp. 1199–1204.

E. A. Kulikova, I. A. Pestunov, and Yu. N. Sinyavskii, “Nonparametric Clustering Algorithm for Processing Large Data Arrays,” in Proc. of 14 All-Russian Conf. on Mathematical Methods of Pattern Recognition (MAKS Press, Moscow, 2009), pp. 149–152.

I. A. Pestunov, V. B. Berikov, and Yu. N. Sinyavskii, “Segmentation of Multispectral Images Based on an Ensemble of Nonparametric Clustering Algorithms,” Vestn. SibGAU, No. 5(31), 56–64 (2010).

I. A. Pestunov, V. B. Berikov, E. A.‘Kulikova, and S. A. Rylov, “Ensemble Clustering Algorithm for Large Datasets,” Avtometriya 47 (3), 49–58 (2011). [Optoelectron., Instrum. Data Process. 47 (3), 245–252 (2011)].

I. A. Pestunov and S. A. Rylov, “Algorithms of Spectral Texture Segmentation of Satellite Images of High Spatial Resolution,” Vestn. KemGU 2 (4(52)), 104–110 (2012).

M. R. Ilango and V. Mohan, “A Survey of Grid Based Clustering Algorithms,” Intern. J. Eng. Sci. Technol. 2 (8), 3441–3446 (2010).

L. Yonggang, W. Yi, “PHA: A Fast Potential-Based Hierarchical Agglomerative Clustering Method,” Patt. Recogn. 46 (5), 1227–1239 (2013).

B. Leclerc, “Description Combinatoire des Ultramétriques,” Math. Sci. Humaines 127 (73), 5–37 (1981).

St. S. Skiena, The Algorithm Design Manual (Springer, 2008).

Cl. F. Olson, “Parallel Algorithms for Hierarchical Clustering,” Parallel Comput. 21 (8), 1313–1325 (1995).

The Matlab Toolbox for Pattern Recognition, http://www.prtools.org.

V. Maurizio, “Principal Classifications Analysis a Method for Generating Consensus Dendrograms and its Application to Three-Way Data,” Comput. Stat. Data Anal. 27 (3), 311–331 (1998).

E. Achtert, H. Kriegel, E. Schubert, and A. Zimek, “Interactive Data Mining with 3D-Parallel-Coordinate-Trees,” in Proc. of ACM Intern. Conf. on Management of Data (SIGMOD), New York., 2013, pp. 1009–1012.

S. A. Rylov, Model of Two-Dimensional Data for Clustering, https://cloud.mail.ru/public/c5f33ae275a8/TestData Rylov 2D Labelled 2472 elements.txt.