Multiagent object-based classifier for high spatial resolution imagery

IEEE Transactions on Geoscience and Remote Sensing

Volumn 52, Issue 2, 2014, Pages 841-847

  Zhong, Yanfei ^a   Zhao, Bei ^a   Zhang, Liangpei ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Global control; high spatial resolution image; multiagent systems; object based classification; segmentation

Indexed keywords

CLASSIFICATION ALGORITHM; GLOBAL CONTROL; GLOBAL CONTROL STRATEGIES; HIERARCHICAL SEGMENTATION; HIGH RESOLUTION REMOTE SENSING; HIGH SPATIAL RESOLUTION IMAGERY; HIGH SPATIAL RESOLUTION IMAGES; OBJECT-BASED CLASSIFICATIONS;

ALGORITHMS; ELECTRIC SHIP EQUIPMENT; IMAGE MATCHING; MULTI AGENT SYSTEMS; PARALLEL ARCHITECTURES; SYNTHESIS (CHEMICAL);

IMAGE SEGMENTATION;

ALGORITHM; IMAGE CLASSIFICATION; IMAGERY; NUMERICAL MODEL; SPATIAL ANALYSIS; SPATIAL RESOLUTION;

EID: 84891040747     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2013.2244604     Document Type: Article

References (40)

1. L. Bruzzone and L. Carlin, "A multilevel context-based system for classification of very high spatial resolution images," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 9, pp. 2587-2600, Sep. 2006. (Pubitemid 44321552)
2. A. P. Carleer, O. Debeir, and E. Wolff, "Assessment of very high spatial resolution satellite image segmentations," Photogram. Eng. Remote Sens., vol. 71, no. 11, pp. 1285-1294, Nov. 2005. (Pubitemid 41567298)
3. T. Blaschke, "Object based image analysis for remote sensing," ISPRS J. Photogram. Remote Sens., vol. 65, no. 1, pp. 2-16, Jan. 2010.
4. J. C. Tilton, Y. Tarabalka, P. M. Montesano, and E. Gofman, "Best merge region-growing segmentation with integrated nonadjacent region object aggregation," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 11, pp. 4454-4467, Nov. 2012.
5. G. J. Hay, T. Blaschke, D. J. Marceau, and A. Bouchard, "A comparison of three image-object methods for the multiscale analysis of landscape structure," ISPRS J. Photogram. Remote Sens., vol. 57, nos. 5-6, pp. 327-345, Apr. 2003. (Pubitemid 36391580)
6. M. Baatz, C. Hoffmann, and G. Willhauck, "Progressing from objectbased to object-oriented image analysis," in Object-Based Image Analysis, T. Blaschke, S. Lang, and G. J. Hay, Eds. New York, USA: Springer-Verlag, 2008, pp. 29-42.
7. L. Vincent and P. Soille, "Watersheds in digital spaces: An efficient algorithm based on immersion simulations," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, no. 6, pp. 583-589, Jun. 1991.
8. P. Li and X. Xiao, "Multispectral image segmentation by a multichannel watershed-based approach," Int. J. Remote Sens., vol. 28, no. 19, pp. 4429-4452, Sep. 2007. (Pubitemid 47471140)
9. D. R. Li, G. F. Zhang, Z. C. Wu, and L. N. Yi, "An edge embedded marker-based watershed algorithm for high spatial resolution remote sensing image segmentation," IEEE Trans. Image Process., vol. 19, no. 10, pp. 2781-2787, Oct. 2010.
10. D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, pp. 603-619, May 2002. (Pubitemid 34550429)
11. M. Baatz and A. Schape, "Multiresolution segmentation-an optimization approach for high quality multi-scale image segmentation," in Proc. 12th Angew. Geographis. Informationsverarbeitung, 2000, pp. 12-13.
12. U. C. Benz, P. Hofmann, G. Willhauck, I. Lingenfelder, and M. Heynen, "Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information," ISPRS J. Photogramm. Remote Sens., vol. 58, nos. 3-4, pp. 239-258, Jan. 2004. (Pubitemid 38106043)
13. J. C. Tilton, "Parallel implementation of the recursive approximation of an unsupervised hierarchical segmentation algorithm," in High Performance Computing in Remote Sensing, A. J. Plaza and C.-I. Chang, Eds. New York, USA: Chapman & Hall, 2007, pp. 1766-1768.
14. X. Huang and L. Zhang, "An adaptive mean-shift analysis approach for object extraction and classification from urban hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 12, pp. 4173-4185, Dec. 2008.
15. M. Neubert, H. Herold, and G. Meinel, "Assessing Image segmentation quality concepts, methods and application," in Object-Based Image Analysis - Spatial Concepts for Knowledge-Driven Remote Sensing Applications, T. Blaschke, G. Hay, and S. Lang, Eds. Berlin, Germany: Springer-Verlag, 2008, pp. 769-784.
16. P. Peng, W. Gao, X. Liu, and Q. Chen, "An improved strategy for object-oriented multi-scale remote sensing image segmentation," in Proc. 1st IEEE Int. Conf. Inf. Sci. Eng., Washington, DC, USA, 2009, pp. 1149-1152.
17. L. Wang, W. P. Sousa, and P. Gong, "Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery," Int. J. Remote Sens., vol. 25, no. 24, pp. 5655-5668, Dec. 2004. (Pubitemid 40008559)
18. Y. Tarabalka, J. A. Benediktsson, J. Chanussot, and J. C. Tilton, "Multiple spectral-spatial classification approach for hyperspectral data," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4122-4132, Nov. 2010.
19. Y. Tarabalka and J. C. Tilton, "Best merge region growing with integrated probabilistic classification for hyperspectral imagery," in Proc. IEEE Geosci. Remote Sens. Symp., Jul. 2011, pp. 3724-3727.
20. M. Bouziani, K. Goita, and H. Dong-Chen, "Rule-based classification of a very high resolution image in an urban environment using multispectral segmentation guided by cartographic data," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 8, pp. 3198-3211, Aug. 2010.
21. K. Bernard, Y. Tarabalka, J. Angulo, J. Chanussot, and J. A. Benediktsson, "Spectral-spatial classification of hyperspectral data based on a stochastic minimum spanning forest approach," IEEE Trans. Image Process., vol. 21, no. 4, pp. 2008-2021, Apr. 2012.
22. Y. Tarabalka and J. Tilton, "Improved hierarchical optimization-based classification of hyperspectral images using shape analysis," in Proc. IEEE Int. Geosci. Remote Sens. Symp., Jul. 2012, pp. 1409-1412.
23. M. Wooldridge, An Introduction to MultiAgent Systems. New York, USA: Wiley, 2002.
24. Y. Shoham and K. Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge, MA, USA: Cambridge Univ. Press, 2009.
25. X. Jin, S. Zhang, and J. Liu, Autonomous Agents and Multi-Agent Systems: Explorations in Learning, Self-Organization and Adaptive Computation. Beijing, China: Tsinghua Univ. Press, 2003.
26. J. Liu and Y. Y. Tang, "Adaptive image segmentation with distributed behavior-based agents," IEEE Trans. Pattern Anal. Mach. Intell., vol. 21, no. 6, pp. 544-551, Jun. 1999.
27. V. Rodin, A. Benzinou, A. Guillaud, P. Ballet, F. Harrouet, J. Tisseau, and J. L. Bihan, "An immune oriented multi-agent system for biological image processing," Pattern Recognit. Soc., vol. 28, pp. 483-494, Apr. 2004.
28. E. G. P. Bovenkamp, J. Dijkstra, J. G. Bosch, and J. H. C. Reiber, "User-Agent Cooperation in Multiagent IVUS Image Segmentation," IEEE Trans. Med. Imag., vol. 28, no. 1, pp. 94-105, Jan. 2009.
29. L. Pigeon, B. Solaiman, T. Toutin, and K. P. B. Thomson, "Multi-agent architecture for map features extraction in multi remotely sensed image fusion," in Proc. IEEE Int. Geosci. Remote Sens. Symp., Jul. 2000, pp. 2840-2842. (Pubitemid 32018790)
30. K. S. Ettabai, I. R. Farah, and M. B. Ahmed, "Multi-agent system for detecting and analysing changes on satellite image sequence," in Proc. IEEE Int. Conf. Ind. Technol., Dec. 2004, pp. 1579-1584. (Pubitemid 41667683)
31. I. R. Farah, W. Boulila, K. S. Ettabaa, and M. Ben Ahmed, "Multiapproach system based on fusion of multispectral images for landcover classification," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 12, pp. 4153-4161, Dec. 2008.
32. S. J. Russell and P. Norvig, Artificial Intelligence - A Modern Approach, 3rd ed. Upper Saddle River, NJ, USA: Prentice-Hall, 2010.
33. C.-C. Chang and C.-J. Lin. (2010). LIBSVM: A Library for Support Vector Machines [Online]. Available: http://www.csie. ntu.edu.tw/cjlin/libsvm
34. J. Li, J. M. Bioucas-Dias, and A. Plaza, "Hyperspectral image segmentation using a new Bayesian approach with active learning," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 10, pp. 3947-3960, Oct. 2011.
35. RHSEG User's Manual: Including the Core RHSEG Open Source Release, HSEGExtract, HSEGReader and HSEGViewer, Version 1.47. (2009) [Online]. Available: http://opensource.gsfc. nasa.gov/projects/HSEG/
36. J. A. Richards and X. Jia, Remote Sensing Digital Image Analysis: An Introduction, 4th ed. New York, USA: Springer-Verlag, 2006.
37. Q. McNemar, "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, vol. 12, no. 2, pp. 153-157, Jun. 1947.
38. Y. Zhong and L. Zhang, "An adaptive artificial immune network for supervised classification of multi-/hyperspectral remote sensing imagery," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 3, pp. 894-909, Oct. 2012.
39. X. Huang, L. Zhang, and P. Li, "Classification of Very High Spatial Resolution Imagery Based on the Fusion of Edge and Multispectral Information," Photogramm. Eng. Remote Sens., vol. 74, no. 11, pp. 1585-1596, Dec. 2008.
40. Definiens Professional 8 Reference Book, Definiens AG, Munchen, Germany, 2010.