Synthesis of remote sensing label fields using a tree-structured hierarchical model

IEEE Transactions on Geoscience and Remote Sensing

Volumn 49, Issue 6 PART 1, 2011, Pages 2060-2070

  Liu, Ying ^a   Wong, Alexander ^a   Fieguth, Paul ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Data synthesis; hierarchical; Markov random field (MRF); remote sensing; sea ice; synthetic aperture radar (SAR)

Indexed keywords

ALTERNATIVE APPROACH; BINARY TREE STRUCTURE; CLASSIFICATION ALGORITHM; COMPLEX DATA; DATA ANALYSIS TOOL; DATA SYNTHESIS; HIERARCHICAL; HIERARCHICAL APPROACH; HIERARCHICAL METHOD; HIERARCHICAL MODEL; MARKOV RANDOM FIELD (MRF); MODEL COMPLEXES; MODELING APPROACH; NONPARAMETRIC METHODS; NONSTATIONARY; RADARSAT; SAR DATA; SIMPLE GEOMETRIES; SYSTEMATIC EVALUATION;

BINARY TREES; DATA REDUCTION; GEOGRAPHIC INFORMATION SYSTEMS; HIERARCHICAL SYSTEMS; IMAGING SYSTEMS; PLANT EXTRACTS; REMOTE SENSING; SEA ICE; SYNTHETIC APERTURES; TREES (MATHEMATICS);

SYNTHETIC APERTURE RADAR;

ALGORITHM; EXPERIMENTAL STUDY; GEOMETRY; GIS; HIERARCHICAL SYSTEM; IMAGE CLASSIFICATION; MARKOV CHAIN; RADARSAT; REMOTE SENSING; SATELLITE DATA; SEA ICE; SEGMENTATION; SYNTHETIC APERTURE RADAR;

EID: 79957629929     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2102765     Document Type: Article

References (42)

1. Q. Yu and D. Clausi, "SAR sea-ice image analysis based on iterative region growing using semantics," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 3919-3931, Dec. 2007. (Pubitemid 350157829)
2. L. Kiage, K. Liu, N.Walker, N. Lam, and O. Huh, "Recent land-cover/use change associated with land degradation in the Lake Baringo catchment, Kenya, East Africa: Evidence from landsat TM and ETM+," Int. J. Remote Sens., vol. 28, no. 19, pp. 4285-4309, Jan. 2007. (Pubitemid 47471129)
3. T. Landmann, C. Herty, S. Dech, and M. Schmidt, "Land cover change analysis within the GLOWA Volta basin in West Africa using 30-meter landsat data snapshots," in Proc. IEEE Int. Geosci. Remote Sens. Symp., 2007, pp. 5298-5301.
4. C. V. der Sande, S. de Jong, and A. de Roo, "A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment," Int. J. Appl. Earth Observ. Geoinform., vol. 4, no. 3, pp. 217-229, Jun. 2003.
5. R. Samadani, "A finite mixture algorithm for finding proportions in SAR images," IEEE Trans. Image Process., vol. 4, no. 8, pp. 1182-1186, Aug. 1995.
6. Q. Redmund, D. Long, and M. Drinkwater, "Polar sea-ice classification using enhanced resolution NSCAT data," in Proc. IEEE Int. Geosci. Remote Sens. Symp., 1998, vol. 4, pp. 1976-1978.
7. J. Karvonen, "Baltic sea ice SAR segmentation and classification using modified pulse-coupled neural networks," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 7, pp. 1566-1574, Jul. 2004.
8. L. Soh, C. Tsatsoulis, D. Gineris, and C. Bertoia, "Arktos: An intelligent system for SAR sea ice image classification," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 1, pp. 229-248, Jan. 2004.
9. R. Kettig and D. Landgrebe, "Classification of multispectral images by extraction and classification of homogeneous objects," IEEE Trans. Geosci. Remote Sens., vol. 14, pp. 19-26, Jan. 1976.
10. F. Melgani and L. Bruzzone, "Classification of hyperspectral remote sensing images with support vector machines," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 8, pp. 1778-1790, Aug. 2004.
11. J. Benediktsson, M. Pesaresi, and K. Amason, "Classification and feature extraction for remote sensing images from urban areas based on morphological transformations," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 9, pp. 1940-1949, Sep. 2003.
12. M. Pesaresi and J. Benediktsson, "A new approach for the morphological segmentation of high-resolution satellite imagery," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 2, pp. 309-320, Feb. 2001. (Pubitemid 32270994)
13. G. Meinel and M. Neubert, "A comparison of segmentation programs for high resolution remote sensing data," Int. Arch. ISPRS, vol. 35, pp. 1097- 1105, 2004.
14. D. Blacknell, A. Blake, P. Lombardo, and C. Oliver, "A comparison of simulation techniques for correlated gamma and K-distributed images for SAR applications," in Proc. IEEE Int. Geosci. Remote Sens. Symp., 1994, vol. 4, pp. 2182-2184.
15. D. Blacknell, "A new method for the simulation of K-distribution clutter," Proc. Inst. Elect. Eng.-Radar Sonar Navig., vol. 141, no. 1, pp. 53-58, Feb. 1994.
16. H. Cantalloube, "Texture synthesis for SAR image simulation," Proc. SPIE, vol. 3497, pp. 242-250, 1998.
17. Y. Wu, C. Wang, H. Zhang, X. Wen, and B. Zhang, "Statistical analysis and simulation of high-resolution SAR ground clutter data," in Proc. IEEE Int. Geosci. Remote Sens. Symp., 2008, vol. 4, pp. 2182-2184.
18. A. A. Efros and T. K. Leung, "Texture synthesis by non-parametric sampling," in Proc. IEEE ICCV, 1999, pp. 1033-1038.
19. L. Liang, C. Liu, Y. Xu, B. Guo, and H. Shum, "Real-time texture synthesis by patch-based sampling," ACMTrans. Graph., vol. 20, no. 3, pp. 127- 150, Jul. 2001. (Pubitemid 33610515)
20. L. Wei and M. Levoy, "Fast texture synthesis using tree-structured vector quantization," in Proc. 27th Annu. Conf. Comp. Graph. Interactive Techn., 2000, pp. 479-488. (Pubitemid 32394012)
21. A. Wong, P. Yu, W. Zhang, and D. Clausi, "Icesynth II: Synthesis of sar sea-ice imagery using region-based local conditional posterior sampling," IEEE Geosci. Remote Sens. Lett., vol. 7, no. 2, pp. 348-351, Apr. 2009.
22. P. Salembier and L. Garrido, "Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval," IEEE Trans. Image Process., vol. 9, no. 4, pp. 561-576, Apr. 2000. (Pubitemid 30594737)
23. C. D'Elia, G. Poggi, and G. Scarpa, "A tree-structured Markov random field model for Bayesian image segmentation," IEEE Trans. Image Process., vol. 12, no. 10, pp. 1259-1273, Oct. 2003.
24. G. Poggi, G. Scarpa, and J. B. Zerubia, "Supervised segmentation of remote sensing images based on a tree-structured MRF model," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 8, pp. 1901-1911, Aug. 2005. (Pubitemid 41329037)
25. G. Scarpa, R. Gaetano, M. Haindl, and J. Zerubia, "Hierarchical multiple Markov chain model for unsupervised texture segmentation," IEEE Trans. Image Process., vol. 18, no. 8, pp. 1830-1843, Aug. 2009.
26. R. Gaetano, G. Scarpa, and G. Poggi, "Hierarchical texture-based segmentation of multiresolution remote-sensing images," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 7, pp. 2129-2141, Jul. 2009.
27. Y. Liu and P. Fieguth, "Parallel hidden hierarchical fields for multi-scale reconstruction," in Proc. EMMCVPR, LNCS, Aug. 2009, pp. 70-83.
28. S. Geman and D. Geman, "Stochastic relaxation, gibbs distributions, and the bayesian restoration of images," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-6, no. 6, pp. 721-741, Nov. 1984. (Pubitemid 15453722)
29. R. Chellappa, "Two-dimensional discrete Gaussian Markov random field models for image processing," in Progress in Pattern Recognition, vol. 2, L. N. Kanal and A. Rosenfeld, Eds. New York: Springer-Verlag, 1985, pp. 79-112.
30. P. Davis, Circulant Matrices. New York: Wiley-Interscience, 1979.
31. H. Rue and L. Held, Gaussian Markov Random Field: Theory and Applications. Boca Raton, FL: CRC Press, 2005.
32. S. Torquato, Random Heterogeneous Materials: Microstructure and Macroscopic Properties. New York: Springer-Verlag, 2002.
33. T. Ojala, M. Pietikainen, and D. Harwood, "A comparative study of texture measures with classification based on feature distributions," Pattern Recognit., vol. 29, no. 1, pp. 51-59, Jan. 1996.
34. C. Graffigne, F. Heitz, P. Pérez, F. Prêux, M. Sigelle, and J. Zerubia, "Hierchical Markov random field models applied to image analysis: A review," Proc. SPIE, vol. 2568, pp. 2-17, Aug. 1994.
35. Z. Kato, M. Berthod, and J. Zerubia, "A hierarchical Markov random field model and multitemperature annealing for parallel image classificaion," Graph. Models Image Process., vol. 58, no. 1, pp. 18-37, Jan. 1996. (Pubitemid 126400280)
36. M. Mignotte, C. Collet, P. Pérez, 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.
37. W. Campaigne, P. Fieguth, and S. Alexander, "Frozen-state hierarchical annealing," in Proc. ICIAR, LNCS, 2006, pp. 41-52. (Pubitemid 44553475)
38. C. B. Atkins, C. A. Bouman, and J. P. Allebach, "Tree-based resolution synthesis," in Proc. Image Process. Image Qual., Image Capture Syst. Conf., 1999, pp. 405-410.
39. C. Won and R. Gray, Stochastic Image Processing. New York: Plenum, 2004.
40. S. Z. Li, Markov Random Field Modeling in Computer Vision. New York: Springer-Verlag, 1995.
41. S. K. Alexander, P. Fieguth, M. Ioannidis, and E. R. Vrscay, "Hierarchical annealing for synthesis of binary porous media images," Math. Geosci., vol. 41, no. 4, pp. 357-378, May 2009.
42. M. Talukdar, O. Torsaeter, and M. Ioannidis, "Stochastic reconstruction of particulate media from two-dimensional images," J. Colloid Interface Sci., vol. 248, no. 2, pp. 419-428, Apr. 2002. (Pubitemid 34969349)