Texture analysis with variational hidden Markov trees

IEEE Transactions on Signal Processing

Volumn 54, Issue 6 I, 2006, Pages 2352-2356

  Dasgupta, Nilanjan ^a   Carin, Lawrence ^a  

^a USA   (United States)

Author keywords

HMT; Kullback Leibler divergence; Texture classification; Variational Bayes

Indexed keywords

MARKOV PROCESSES; NUMERICAL ANALYSIS; PATTERN RECOGNITION; TREES (MATHEMATICS); WAVELET TRANSFORMS;

BAYES FORMULATION; HIDDEN MARKOV TREE; TEXTURE ANALYSIS;

IMAGE ANALYSIS;

EID: 33744529620     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2006.872588     Document Type: Article

References (13)

1. A. K. Jain, "Advances in mathematical models for image processing," Proc. IEEE, vol. 69, no. 5, pp. 502-528, May 1981.
2. S. Mallat, A Wavelet Tour of Signal Processing. New York: Academic, 1998.
3. M. S. Crouse, R. D. Nowak, and R. G. Baraniuk, "Wavelet-based statistical signal processing using hidden Markov models," IEEE Trans. Signal Process., vol. 46, no. 4, pp. 886-902, Apr. 1998.
4. B. Hendricks, H. Choi, and R. Baraniuk, "Analysis of texture segmentation using wavelet-domain hidden Markov trees," presented at the Asilomar Conf. Signals, Systems, Computers, Pacific Grove, CA, Oct. 1999.
5. G. Fan and X.-G. Xia, "Wavelet-based texture analysis and synthesis using hidden Markov models," IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., vol. 50, no. 1, pp. 106-120, Jan. 2003.
6. M. N. Do and M. Vetterli, "Rotation invariant texture characterization and retrieval using steerable wavelet-domain hidden Markov models," IEEE Trans. Multimedia, vol. 4, no. 4, pp. 517-527, Dec. 2002.
7. H. Attias, "A variational Bayesian framework for graphical models," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 2000, vol. 12, pp. 209-215.
8. D. Gamerman, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. Boca Raton, FL: CRC, 1997.
9. P. S. Laplace, "Memoir on the probability causes of events," Statist. Sci., vol. 1, no. 19, pp. 364-378, 1774.
10. S. Kullback and R. A. Leibler, "On information and sufficiency," Ann. Stat., vol. 22, pp. 79-86, 1951.
11. M. Opper and D. Saad, Eds., Advanced Mean Field Methods. Cambridge, MA: MIT Press, 2001.
12. J. Winn and C. M. Bishop, "Variational message passing," J. Mach. Learn. Res., vol. 6, pp. 661-694.
13. University of Southern California Image Database [Online]. Available: http://sipi.usc.edu