A genetic expectation-maximization method for unsupervised change detection in multitemporal SAR imagery

International Journal of Remote Sensing

Volumn 30, Issue 24, 2009, Pages 6591-6610

  Bazi, Yakoub ^a   Melgani, Farid ^b   Bruzzone, Lorenzo ^b   Vernazza, Gianni ^c  

^a JOUF UNIVERSITY   (Saudi Arabia)

^b UNIVERSITY OF TRENTO   (Italy)

^c UNIVERSITY OF GENOA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; IMAGE ANALYSIS; MAXIMUM PRINCIPLE; STATISTICAL METHODS; SYNTHETIC APERTURE RADAR;

BAYESIAN INFORMATION CRITERION; CONTEXTUAL INFORMATION; EXPECTATION-MAXIMIZATION ALGORITHMS; EXPECTATION-MAXIMIZATION METHOD; GENERALIZED GAUSSIAN DISTRIBUTION; GENETIC ALGORITHM (GAS); MULTI-TEMPORAL SAR IMAGES; UNSUPERVISED CHANGE DETECTION;

RADAR IMAGING;

BAYESIAN ANALYSIS; DETECTION METHOD; GAUSSIAN METHOD; GENETIC ALGORITHM; HISTOGRAM; MARKOV CHAIN; PARAMETERIZATION; SATELLITE IMAGERY; SPATIAL DATA; SYNTHETIC APERTURE RADAR;

EID: 77449115217     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160902882538     Document Type: Article

References (38)

1. ABRAMOWITZ, M. and STEGUN, I.A., 1972, Handbook of Mathematical Functions with Formulas, Graphs and Mathematical Tables (New York: Dover Publications).
2. AKAIKE, H., 1974, A new look at the statistical model identification. IEEE Transactions on Automatic Control, AC-19, pp. 716-723.
3. BAZI, Y. and MELGANI, F., 2006, Toward an optimal SVM classification system for hyperspec-tral remote sensing images. IEEE Transactions on Geoscience & Remote Sensing, 44, pp. 3374-3385.
4. BAZI, Y., BUZZONE, L. and MELGANI, F., 2005, An unsupervised approach based on the generalized gaussian model to automatic change detection in multitemporal SAR images. IEEE Transactions on Geoscience & Remote Sensing, 43, pp. 874-887.
5. BAZI, Y., BUZZONE, L. and MELGANI, F., 2006, Automatic identification of the number and values of decision thresholds in the log-ratio image for change detection in SAR images. IEEE Geoscience & Remote Sensing Letters, 3, pp. 349-353.
6. BOVOLO, F. and BRUZZONE, L., 2005, A detail-preserving scale-driven approach to change detection in multitemporal SAR images. IEEE Transactions on Geoscience & Remote Sensing, 43, pp. 2963-2972.
7. BOZDOGAN, H., 1993, Choosing the number of component clusters in the mixture model using a new informational complexity criterion of the inverse-Fisher information matrix. In O. Opitz, B. Lausen and R. Klar (Eds) Information and Classification, pp. 40-54 (Berlin: Springer-Verlag).
8. BRUZZONE, L. and PRIETO, D.F., 2000a, A minimum-cost thresholding technique for unsu-pervised change detection. International Journal of Remote Sensing, 21, pp. 3539-3544.
9. BRUZZONE, L. and PRIETO, D. F., 2000b, Automatic analysis of the difference image for unsupervised change detection. IEEE Transactions on Geoscience & Remote Sensing, 38, pp. 1171-1182.
10. BRUZZONE, L. and COSSU, R., 2002, Analysis of multitemporal remote-sensing images for change detection: Bayesian thresholding approaches. In E. Binaghi, P.A. Brivio and S.B. Serpico (Eds) Geospatial Pattern Recognition, 15, pp. 319-336 (Kerala, India: Research Signpost/Transworld Research).
11. BRUZZONE, L. and PRIETO, D.F., 2002, An adaptive semi-parametric and context-based approach to unsupervised change detection in multitemporal remote sensing images. IEEE Transactions on Image Processing, 11, pp. 452-466.
12. BUJOR, F.T., NICOLAS, J.-M., TROUVÉ, E. and RUDANT, J.-P., 2003, Application of logcumulants to change detection in multi-temporal SAR images. In Proceedings of the IEEE-IGARSS 2003, Toulouse, France, 21-25 July 2003, 2, pp. 1386-1388.
13. CARINCOTTE, C., DERRODE, S. and BOURENNANE, S., 2006, Unsupervised change detection on SAR images using fuzzy hidden markov chains. IEEE Transactions on Geoscience & Remote Sensing, 44, pp. 432-441.
14. CAVANAUGH, E., 1999, A large-sample model selection criterion based on Kullback's symmetric divergence. Statistics & Probability Letters, 42, pp. 333-343.
15. CIHLAR, J, PULTZ, T.J. and GRAY, A.L., 1992, Change detection with synthetic aperture radar. International Journal of Remote Sensing, 13, pp. 401-414.
16. DEKKER, R.J., 1998, Speckle filtering in satellite SAR change detection imagery. International Journal of Remote Sensing, 19, pp. 1133-1146.
17. DEMPSTER, P., LAIRD, N.M. and RUBIN, D.B., 1977, Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 39, pp. 1-38.
18. DO, M.N. and VETTERLI, M., 2002, Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance. IEEE Transactions on Image Processing, 11, pp. 146-158.
19. DUBES, R.C. and JAIN, A.K., 1989, Random field models in image analysis. Journal of Applied Statistics, 16, pp. 131-163.
20. FWU, J.K. and DJURIĆ, P.M., 1997, EM algorithm for image segmentation initialized by a tree structure scheme. IEEE Transactions on Image Processing, 6, pp. 349-352.
21. GOLDBERG, D.E., 1989, Genetic Algorithms in Search, Optimization and Machine Learning (Reading, MA: Addison-Wesley).
22. GROVER, K. and QUEGAN, S., 1999, Quantitative estimation of tropical forest cover by SAR. IEEE Transactions on Geoscience & Remote Sensing, 37, pp. 479-490.
23. HASTIE, T. and TIBSHIRANI, R., 1996, Discriminant analysis by Gaussian Mixtures. Journal of the Royal Statistical Society (B), 58, pp. 155-176.
24. LOPES, A., TOUZI, R. and NEZRY, E., 1990, Adaptive speckle filters and scene heterogeneity. IEEE Transactions on Geoscience & Remote Sensing, 28, pp. 992-1000.
25. MCLACHLAN, G. and KRISHNAN, T., 1997, The EM algorithm and Extensions (New York: John Wiley & Sons).
26. MCLACHLAN, G. and PEEL, D., 2000, Finite mixture models (New York: John Wiley & Sons).
27. MELGANI, F. and BAZI, Y., 2006, Markovian fusion approach to robust unsupervised change detection in remotely sensed imagery. IEEE Geoscience & Remote Sensing Letters, 4, pp. 457-461.
28. MELGANI, F. and SERPICO, S.B., 2003, A Markov random field approach to spatio-temporal contextual image classification. IEEE Transactions on Geoscience & Remote Sensing, 41, pp. 2478-2487.
29. MELGANI, F., MOSER, G. and SERPICO, S.B., 2002, Unsupervised change-detection methods for remote-sensing data. Optical Engineering, 41, pp. 3288-3297.
30. PRESS, W.H., FLANNERY, B.P., TEUKOLSKY, S.A. and VETTERLING, W.T., 1988, Numerical Recipes in C: the Art of Scientific Computing (New York: Cambridge University Press).
31. RIGNOT, E.J.M. and VAN ZYL, J.J., 1993, Change detection techniques for ERS-1 SAR data. IEEE Transactions on Geoscience & Remote Sensing, 31, pp. 896-906.
32. RISSANEN, J., 1978, Modeling by shortest data description. Automatica, 14, pp. 465-471.
33. ROBERTS, S., HUSMEIER, D., REZEK, I. and PENNY, W., 1998, Bayesian approaches to Gaussian mixture modeling. IEEE Trans. Pattern Analysis and Machine Intelligence, 20, pp. 1133-1142.
34. SCHWARZ, G., 1978, Estimating the dimension of a model. Annals of Statistics, 6, pp. 461-464.
35. SMITS, P.C. and DELLEPIANE, S.G., 1997, Synthetic aperture radar image segmentation by a detail preserving Markov random field approach. IEEE Transactions on Geoscience & Remote Sensing, 35, pp. 844-857.
36. TRAN, T.N., WEHRENS, R., HOEKMAN, D.H. and BUYDENS, L.M.C., 2003, Initialization of Markov random field clustering of large remote sensing images. IEEE Transactions on Geoscience & Remote Sensing, 43, pp. 1912-1919.
37. VILLASENOR, J.D., FATLAND, D.R. and HINZMAN, L.D., 1993, Change detection on Alaska's north slope using repeat-pass ERS-1 SAR imagery. IEEE Transactions on Geoscience & Remote Sensing, 31, pp. 227-236.
38. WALLACE, C. and FREEMAN, P., 1987, Estimation and inference by compact coding. Journal of the Royal Statistical Society (B) (Methodological), 49, pp. 240-265.