MRF model parameter estimation for contextual supervised classification of remote-sensing images

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 1, Issue , 2005, Pages 308-311

  Moser, Gabriele ^a   Serpico, Sebastiano B ^a   Causa, Federico ^a  

^a UNIVERSITY OF GENOA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; IMAGE ANALYSIS; MARKOV PROCESSES; OPTIMIZATION; PROBLEM SOLVING; REMOTE SENSING;

BINARY CLASSIFICATION; HO-KASHYAP ALGORITHMS; MARKOV RANDOM FIELD (MRF);

PARAMETER ESTIMATION;

EID: 33745727802     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2005.1526169     Document Type: Conference Paper

References (12)

1. R. C. Dubes and A. K. Jain, "Random Field models in image analysis," J. Appl. Stat., vol. 16, pp. 131-163, 1989.
2. S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, pp. 721-741, 1984.
3. Q. Jackson and D. Landgrebe, "Adaptive Bayesian contextual classification based on Markov Random Fields," IEEE Transactions on Geoscience and Remote Sensing, vol. 40, no. 11, pp. 2454-2463, 2002.
4. F. Melgani and S. B. Serpico, "A Markov random field approach to spatio-temporal contextual image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 11, pp. 2478-2487, 2003.
5. A. H. S. Solberg, T. Taxt, and A. K. Jain, "A Markov Random Field model for classification of multisource satellite imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 34, no. 1, pp. 100-113, 1996.
6. L. Bruzzone and D. F. Prieto, "Automatic analysis of the difference image for unsupervised change detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 3, pp. 1171-1182, 2000.
7. M. V. Ibanez and A. Simo', "Parameter estimation in Markov random field image modeling with imperfect observations. A comparative study," Pattern Recognition Letters, vol. 24, no. 14, pp. 2377-2389, 2003.
8. J. T. Tou and R. C. Gonzalez, Pattern Recognition Principles. MA: Addison-Wesley Publ. Comp., 1974.
9. K. Fukunaga, Introduction to statistical pattern recognition. 2nd edition, Academic Press, 1990.
10. D. A. Landgrebe, Signal Theory Methods in Multispectral Remote Sensing. Wiley-InterScience, 2003.
11. M. Datcu, F. Melgani, A. Piardi, and S. B. Serpico, "Multisource data classification with dependence trees," IEEE Transactions on Geoscience and Remote Sensing, vol. 40, no. 3, pp. 609-617, 2002.
12. G. Moser, J. Zerubia, and S. B. Serpico, "Dictionary-based Stochastic Expectation-Maximization for SAR amplitude probability density function estimation," INRIA, Research Report 5154, Mar. 2004. [Online]. Available: http://www.inria.fr/rrrt/rr-5154.html