Unsupervised bayesian image segmentation using wavelet-domain hidden Markov models

IEEE International Conference on Image Processing

Volumn 2, Issue , 2003, Pages 423-426

  Song, Xiaomu ^a   Fan, Guoliang ^a  

^a Oklahoma State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE TEXTURES; SUPERVISED ALGORITHMS; WAVELET SUBBANDS;

ALGORITHMS; COMPUTER SIMULATION; FEATURE EXTRACTION; MARKOV PROCESSES; OPTIMIZATION; PARAMETER ESTIMATION; STATISTICAL METHODS; WAVELET TRANSFORMS;

IMAGE SEGMENTATION;

EID: 0345566158     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. M. S. Crouse, R. D. Nowak, and R. G. Baraniuk, "Wavelet-based statistical signal processing using hidden Markov models," IEEE Trans. Signal Processing, vol. 46, no. 4, pp. 886-902, April 1998.
2. J. K. Romberg, H. Choi, and R. G. Baraniuk, "Bayesian tree-structured image modeling using wavelet-domain hidden Markov models," IEEE Trans. Image Processing, vol. 10, no. 7, pp. 1056-1068, July 2001.
3. G. Fan and X.-G. Xia, "Wavelet-based texture analysis and synthesis using hidden Markov models," IEEE Trans. Circuits and Systems, Part I, vol. 50, no. 1, pp. 106-120, Jan. 2003.
4. C. A. Bouman and M. Shapiro, "A multiscale random field model for Bayesian image segmentation," IEEE Trans. Image Processing, vol. 3, no. 2, pp. 162-177, March 1994.
5. H. Cheng and C. A. Bouman, "Multiscale Bayesian segmentation using a trainable context model," IEEE Trans. Image Processing, vol. 10, no. 4, pp. 511-525, April 2001.
6. G. Fan and X.-G. Xia, "A joint multi-context and multiscale approach to Bayesian image segmentation," IEEE Trans. Geoscience and Remote Sensing, vol. 39, no. 12, Dec. 2001.
7. H. Choi and R. Baraniuk, "Multiscale image segmentation using wavelet-domain hidden markov models," IEEE Trans. Image Processing, vol. 10, no. 9, pp. 1309-1321, 2001.
8. T. N. Pappas, "Maximun-likelihood parameter estimation for unsupervised stochastic model-based image segmentation," IEEE Trans. Image Processing, vol. 3, no. 4, pp. 404-420, July 1994.
9. J. Zhang, J. W. Modestino, and D. A. Langan, "Maximun-likelihood parameter estimation for unsupervised stochastic model-based image segmentation," IEEE Trans. Image Processing, vol. 3, no. 4, pp. 404-420, July 1994.
10. B. S. Manjunath and R. Chellappa, "Unsupervised texture segmentation using Markov random field models," IEEE Trans. Pattern Anal. and Machine Intell., vol. 13, no. 5, pp. 478-482, May 1991.
11. H. Noda, M. N. Shirazi, and E. Kawaguchi, "An MRF model-based method for unsupervised textured image segmentation," in Proc. of the 13th International Conference on Pattern Recognition, August 1996, vol. 2, pp. 765-769.
12. E. P. Simoncelli and J. Portilla, "Texture characterization via joint statistics of wavelet coefficient magnitudes," in Proc. of IEEE Int'l Conf. Image Proc., Oct. 1998, vol. 1, pp. 62-66.