A context-sensitive clustering technique based on graph-cut initialization and expectation-maximization algorithm

IEEE Geoscience and Remote Sensing Letters

Volumn 5, Issue 1, 2008, Pages 21-25

  Tyagi, Mayank ^b   Bovolo, Francesca ^a,c   Mehra, Ankit K ^b   Chaudhuri, Subhasis ^b   Bruzzone, Lorenzo ^a,c  

^a IEEE

^b INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

^c UNIVERSITY OF TRENTO   (Italy)

Author keywords

Clustering; Expectation maximization (EM) algorithm; Remote sensing; Segmentation; Unsupervised classification

Indexed keywords

CLASSIFICATION (OF INFORMATION); FUZZY RULES; GRAPH THEORY; REMOTE SENSING; STATISTICAL METHODS;

EXPECTATION-MAXIMIZATION (EM) ALGORITHMS; UNSUPERVISED CLASSIFICATION;

CLUSTERING ALGORITHMS;

EID: 38349123042     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2007.905119     Document Type: Article

References (13)

1. R. Duda and P. Hart, Pattern Classification and Scene Analysis. New York: Wiley, 2001.
2. J. Bezedek, R. Ehrlich, and W. Full, "FCM: The fuzzy c-means clustering algorithm," Comput. Geosci., vol. 10, no. 2/3, pp. 191-203, 1984.
3. F. Dell'Acqua and P. Gamba, "Detection of urban structures in SAR images by robust fuzzy clustering algorithms: The example of street tracking," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 10, pp. 2287-2297, Oct. 2001.
4. Y. Zhong, L. Zhang, B. Huang, and P. Li, "An unsupervised artificial immune classifier for multi/hyperspectral remote sensing imagery," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 2, pp. 420-431, Feb. 2006.
5. S. Le Hegarat-Mascle, I. Bloch, and D. Vidal-Madjar, "Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing," IEEE Trans. Geosci. Remote Sens., vol. 35, no. 4, pp. 1018-1031, Jul. 1997.
6. A. Baraldi and F. Parmiggiani, "A neural network for unsupervised categorization of multivalued input patterns: An application to satellite image clustering," IEEE Trans. Geosci. Remote Sens., vol. 33, no. 2, pp. 305-316, Mar. 1995.
7. T. Tran, R. Wehrens, D. Hoekman, and L. Buydens, "Initialization of Markov random field clustering of large remote sensing images," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 8, pp. 1912-1919, Aug. 2005.
8. S. Lee, "Efficient multistage approach for unsupervised image classification," in Proc. IEEE Int. Geosci. Remote Sens. Symp., 2004, vol. 3, pp. 1581-1584.
9. V. Cherkassky and F. Mulier, Learning From Data: Concepts, Theory, and Methods. New York: Wiley, 1998.
10. L. Bruzzone and D. F. Prieto, "Unsupervised retraining of a maximum likelihood classifier for the analysis of multitemporal remote sensing images," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 2, pp. 456-460, Feb. 2001.
11. P. Felzenszwalb and D. Huttenlocher, "Efficient graph-based image segmentation," Int. J. Comput. Vis., vol. 59, no. 2, pp. 167-181, Sep. 2004.
12. T. Moon, "The expectation-maximization algorithm," IEEE Signal Process. Mag., vol. 13, no. 6, pp. 47-60, Nov. 1996.
13. A. Dempster, N. Laird, and D. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. R. Stat. Soc., vol. 39, no. 1, pp. 1-38, 1977.