Pixon-based image segmentation with Markov random fields

IEEE Transactions on Image Processing

Volumn 12, Issue 12, 2003, Pages 1552-1559

  Yang, Faguo ^a   Jiang, Tianzi ^a,b  

^a INSTITUTE OF AUTOMATION   (China)

^b University of Houston   (United States)

Author keywords

Image segmentation; Markov random fields; Pixon

Indexed keywords

ANISOTROPY; DIFFUSION; DYNAMIC PROGRAMMING; FUZZY CONTROL; MARKOV PROCESSES; OPTIMIZATION; PROBLEM SOLVING;

FUZZY PIXON; IMAGE INTERPRETATION; MARKOV RANDOM FIELDS; PIXON;

IMAGE SEGMENTATION;

EID: 10844286508     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2003.817242     Document Type: Article

References (29)

1. P. K. Sahoo, S. Soltani, and A. K. C. Wong, "A survey of thresholding techniques," in Comput. Vis. Graph. Image Process., vol. 41, 1988, pp. 233-260.
2. J. K. Udupa and S. Samarasekera, "Fuzzy connectedness and object definition: Theory, algorithms and applications in image segmentation," in Graph. Mod. Image Process., vol. 58, 1996, pp. 246-261.
3. G. B. Coleman and H. C. Andrews, "Image segmentation by clustering," Proc. IEEE, vol 5, pp. 773-785, 1979.
4. J C. Bezdek, L. O. Hall, and L. P. Clarke, "Review of MR image segmentation techniques using pattern recognition," Med. Phys., vol. 20, pp. 1033-1048, 1993.
5. D. L. Vilarino, V. M. Brea. D. Cabello, and J. M. Pardo, "Discrete-time CNN for image segmentation by active contours," Pattern Recognit. Lett., vol. 19, pp. 721-734, 1998.
6. V. Caselles, R. Kimmel, and G. Sapiro, "Geodesic active contours," Int. J. Comput. Vis , vol. 22, pp. 61-79, 1997
7. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes, Active contour models," Int. J. Comput. Vis., vol. 1, no. 4, pp. 321-331, 1988.
8. R. C. Dubes and A. K Jain, "Random field models in image analysis," J. Appl. Statist., vol. 16, no. 2, pp. 131-164, 1989.
9. K. Abend, T. Harley, and L. N. Kanal, "Classification of binary random patterns," IEEE Trans. Inform. Theory, vol. IT-11, pp. 538-544, 1965.
10. G. R. Cross and A. K. Jain, "Markov random field texture models," IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-5, pp. 25-39, 1983.
11. S. Geman and D. Geman, "Stochastic relaxiation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Machine Intell, vol. 6, no 6, pp. 721-741, 1984.
12. H. Derin and H. Elliott, "Modeling and segmentation of noisy and textured images using Gibbs random fields," IEEE Trans. Pattern Anal. Machine Intell, vol. PAMI-9, pp. 39-55, 1987
13. S. Lakshmanan and H. Derin, "Simultaneous parameter estimation and segmentation of Gibbs random fields using simulated annealing," IEEE Trans. Pattern Anal. Machine Intell., vol. 11, no. 8, pp. 799-813, 1989.
14. Z. Kato, J. Zerubia, and M. Berthod, "Unsupervised parallel image classification using Markovian models," Pattern Recognit., vol. 32, pp. 591-604, 1999.
15. I. M. Elfadel and R. W. Picard, "Gibbs random fields, cooccurrences, and texture modeling," IEEE Trans Pattern Anal. Machine Intell., vol 16, pp. 24-37, 1994.
16. D. K. Panjwani and G. Healey, "Markov random field models for unsupervised segmentation of textured color images," IEEE Trans. Pattern Anal. Machine Intell., vol. 17, pp. 939-954, 1995.
17. P. Andrey and P. Tarroux, "Unsupervised segmentation of Markov random field modeled textured images using selectionist relaxation," IEEE Trans. Pattern Anal. Machine Intell., vol. 20, pp. 252-262, 1998.
18. J. W. Modestino and J. Zhang, "A Markov random field model-based approach to image interpretation," IEEE Trans. Pattern Anal. Machine Intell., vol. 14, pp. 606-615, 1992.
19. I. Y. Kim and H. S. Yang, "A systematic way for region-based image segmentation based on Markov random field model," Pattern Recognit. Lett., vol. 15, pp. 969-976, 1994
20. X Descombes and F. Kruggel, "A Markov pixon information approach for low-level image description," IEEE Trans. Pattern Anal. Machine Intell., vol. 21, pp. 482-494, 1999.
21. R K. Piña and R. C. Pueter, "Bayesian image reconstruction: The pixon and optimal image modeling," P. A. S. P., vol. 105, pp. 630-637, 1993.
22. R. C. Puetter, "Pixon-based multiresolution image reconstruction and the quantification of picture information content," Int. J. Imag Syst. Technol., vol. 6, pp. 314-331, 1995.
23. P. Perona and J. Malik, "Scale-space filtering and edge detection using anisotropic diffusion," IEEE Trans Pattern Anal. Machine Intell., vol. 12, no 7, pp. 629-639, 1990.
24. [241 M. Suk, "A new image segmentation technique based on partition mode test," Pattern Recognit., vol. 16, pp. 469-480, 1983.
25. R. Kindermann and J. L. Snell, Markov Random Fields and Their Applications. Providence, RI: Amer. Math. Soc., 1980
26. [261 J. C. Rajapakse, J. N. Giedd, and J. L. Rapoport, "Statistical approach to segmentation of single-channel celebral MR images," IEEE Trans. Med. Imag., vol. 16, pp. 176-186, 1997.
27. S. Kirkpatrick, C. D. Gelatt Jr, and M. P. Vecchi, "Optimization by simulated annealing," Science, vol 220, pp. 621-680, 1983.
28. D. E. Goldber, Genetic Algorithm in Search, Optimization and Machine Learning. Reading, MA: Addison-Wesley, 1992.
29. D. Cvijovic and J. Klinowski, "Taboo search: An approach to the multiple minima problem," Science, vol. 267, pp. 664-666, 1995.