Hierarchical Conditional Random Fields Model for Semisupervised SAR Image Segmentation

IEEE Transactions on Geoscience and Remote Sensing

Volumn 53, Issue 9, 2015, Pages 4933-4951

  Zhang, Peng ^a   Li, Ming ^a   Wu, Yan ^a   Li, Hejing ^a  

^a XIDIAN UNIVERSITY   (China)

Author keywords

Hierarchical conditional random field (HIECRF) model; hierarchical inference; multiresolution analysis; semisupervised synthetic aperture radar (SAR) image segmentation

Indexed keywords

APPROXIMATION ALGORITHMS; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE SEGMENTATION; INFERENCE ENGINES; MULTIRESOLUTION ANALYSIS; RADAR; RANDOM PROCESSES; SEMANTICS; SYNTHETIC APERTURE RADAR;

CONDITIONAL INDEPENDENCES; CONDITIONAL RANDOM FIELD; DISCRIMINATIVE MODELS; HIERARCHICAL INFERENCE; MEAN FIELD APPROXIMATION; SAR IMAGE SEGMENTATION; SEMI-SUPERVISED SEGMENTATIONS; STRUCTURE INFORMATION;

RADAR IMAGING;

HIERARCHICAL SYSTEM; IMAGE CLASSIFICATION; IMAGE PROCESSING; IMAGE RESOLUTION; SCATTERING; SYNTHETIC APERTURE RADAR;

EID: 85027934756     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2015.2413905     Document Type: Article

References (32)

1. S. Kumar and M. Hebert, "Discriminative random fields," Int. J. Comput. Vis., vol. 68, no. 2, pp. 179-202, Jun. 2006.
2. P. Zhong and R. S. Wang, "A multiple conditional random fields ensemble model for urban area detection in remote sensing optical images," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 3978-3988, Dec. 2007.
3. P. Kohli, L. Ladicky, and P. H. S. Torr, "Robust high order potentials for enforcing label consistency," Int. J. Comput. Vis., vol. 68, no. 3, pp. 302-324, May 2009.
4. S. Kumar and M. Hebert, "A hierarchical field framework for unified context-based classification," in Proc. IEEE Int. Conf. Computer Vision, 2005, vol. 2, pp. 1284-1291.
5. P. Zhong and R. S. Wang, "Learning sparse CRFs for feature selection and classification of hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 12, pp. 4186-4197, Dec. 2008.
6. X. He, R. S. Zemel, and M. A. Carreira-Perpinan, "Multiscale conditional random fields for image labeling," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2005, vol. 2, pp. 695-702.
7. T. Toyoda and O. Hasegawa, "Random field model for integration of local information and global information," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 8, pp. 1483-1489, Aug. 2008.
8. P. Zhang et al., "Unsupervised SAR image segmentation using a hierarchical TMF model," IEEE Geosci. Remote Sens. Lett., vol. 10, no. 5, pp. 971-975, Sep. 2013.
9. A. Katartzis, I. Vanhamel, and H. Sahli, "A hierarchical Markovian model for multiscale region-based classification of vector-valued images," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 3, pp. 548-558, Mar. 2005.
10. M. Mignotte, C. Collet, P. Perez, and P. Bouthemy, "Sonar image segmentation using an unsupervised hierarchical MRF model," IEEE Trans. Image Process., vol. 9, no. 7, pp. 1216-1231, Jul. 2000.
11. C. Tison, J. M. Nicolas, F. Tupin, and H. Maitre, "A new statistical model for Markovian classification of urban areas in high-resolution SAR images," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 10, pp. 2046-2057, Oct. 2004.
12. P. Zhang et al., Unsupervised multi-class segmentation of SAR images using fuzzy triplet Markov fields model, Pattern Recognit., vol. 45, no. 11, pp. 4018-4033, Nov. 2012.
13. S. Z. Li, Markov Random Field Modeling in Image Analysis. London, U.K.: Springer-Verlag, 2009.
14. Q. Cheng, P. K. Varshney, and M. K. Arora, "Logistic regression for feature selection and soft classification of remote sensing data," IEEE Geosci. Remote Sens. Lett., vol. 3, no. 4, pp. 491-494, Oct. 2006.
15. S. C. Zhu, "Statistical modeling and conceptualization of visual patterns," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 6, pp. 1-22, Jun. 2003.
16. C. C. Chang and C. J. Lin, "LIBSVM: A library for support vector machines," ACMTrans. Intell. Syst. Technol., vol. 2, no. 3, pp. 27:1-27:27, Apr. 2011.
17. T. F. Wu, C. J. Lin, and R. C. Weng, "Probability Estimates for Multiclass Classification by Pairwise Coupling," J. Mach. Learn. Res., vol. 5, pp. 975-1005, 2004.
18. R. J. Dekker, "Texture analysis and classification of ERS SAR images for map updating of urban areas in The Netherlands," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 9, pp. 1950-1958, Sep. 2003.
19. R. Jobanputra and D. A. Clausi, "Preserving boundaries for image texture segmentation using grey level co-occurring probabilities," Pattern Recognit., vol. 39, no. 2, pp. 234-245, Feb. 2006.
20. R. Fjortoft, A. Lopes, P. Marthon, and C. E. Cubero, "An optimal multiedge detector for SAR image segmentation," IEEE Trans. Geosci. Remote Sens., vol. 36, no. 3, pp. 793-802, May 1998.
21. H. C. Li, W. Hong, Y. R. Wu, and P. Z. Fan, "An efficient and flexible statistical model based on generalized gamma distribution for amplitude SAR images," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 6, pp. 2711-2722, Jun. 2010.
22. K. S. Song, "Globally convergent algorithms for estimating generalized gamma distributions in fast signal and image processing," IEEE Trans. Image Process., vol. 17, no. 8, pp. 1233-1250, Aug. 2008.
23. M. L. Comer and E. J. Delp, "The EM/MPM algorithm for segmentation of textured images: analysis and further experimental results," IEEE Trans. Image Process., vol. 9, no. 10, pp. 1731-1744, Oct. 2000.
24. J. M. Laferte, P. Perez, and F. Heitz, "Discrete Markov modeling and inference on the quad-tree," IEEE Trans. Image Process., vol. 9, no. 3, pp. 390-404, Mar. 2000.
25. G. Celeux, F. Forbes, and N. Peyrard, "EM procedures using mean field-like approximations for Markov model-based image segmentation," INRIA, Grenoble, France, Tech. Rep. 4105, 2001. [Online]. Available: http://hal.inria.fr/inria-00072526/en/
26. E. Bratsolis and M. Sigelle, "Image relaxation using Potts model with a fast deterministic method," J. Opt. Soc. Amer. A, Opt. Image Sci., vol. 14, no. 5, pp. 1033-1043, May 1997.
27. C. M. Bishop, Pattern Recognition and Machine Learning. NewYork, NY, USA: Springer-Verlag, 2006, ch. 1, pp. 32-33.
28. Y. Wu, P. Zhang, and M. Li, "SAR image multiclass segmentation using a multiscale and multidirection triplet Markov fields model in nonsubsampled contourlet transform domain," Inf. Fusion, vol. 14, no. 4, pp. 441-449, Oct. 2013.
29. H. Derin and H. Elliott, "Modeling and segmentation of speckled images using complex data," IEEE Trans. Geosci. Remote Sens., vol. 28, no. 1, pp. 2711-2722, Jan. 1990.
30. Y. H. Wang, C. Z. Han, and F. Tupin, "PolSAR data segmentation by combining tensor space cluster analysis and Markovian framework," IEEE Geosci. Remote Sens. Lett., vol. 7, no. 1, pp. 210-214, Jan. 2010.
31. H. W. Deng and D. A. Clausi, "Unsupervised image segmentation using a simple MRF model with a new implementation scheme," Pattern Recognit., vol. 37, no. 12, pp. 2323-2335, Dec. 2004.
32. O. D. Hondt, C. L. Martinez, L. F. Famil, and E. Pottier, "Spatially nonstationary anistropic texture analysis in SAR images," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 3905-3918, Dec. 2007.