Multi-feature adaptive classifiers for SAR image segmentation

Neurocomputing

Volumn 14, Issue 4, 1997, Pages 345-363

  Ceccarelli, Michele ^a   Petrosino, Alfredo ^a  

^a CNR   (Italy)

Author keywords

ensemble classification; image segmentation; neural networks

Indexed keywords

FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE QUALITY; IMAGE SEGMENTATION; PATTERN RECOGNITION SYSTEMS; SENSOR DATA FUSION; SYNTHETIC APERTURE RADAR;

MULTIFEATURE ADAPTIVE CLASSIFIERS;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; PRIORITY JOURNAL;

EID: 0031579684     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(96)00038-0     Document Type: Article

References (37)

1. [1] M.R. Azimi-Sadjadi, S. Ghaloum and R. Zoughi, Terrain classification in SAR images using principal component analysis and neural networks, IEEE Trans. Geoscience and Remote Sensing 31 (2) (1993) 511-515.
2. [2] M.J. Bastiaans, A Sampling Theorem for the complex spectrogram and Gabor's expansion of a signal in Gaussian elementary signals, Optical Engineering 20 (1981) 594-598.
3. [3] R. Battiti and A.M. Colla, On the cooperation of multiple nets for pattern recognition, in: E.R. Caianiello, ed., Proc. 5th Italian Workshop on Neural Nets World Scientific Publishing, (1992).
4. [4] R. Battiti and A.M. Colla, Democracy in neural networks: Voting schemes for classification, Neural Networks (1994) to appear.
5. [5] W.G. Baxt, Improving the accuracy of an artificial neural network using multiple differently trained networks, Neural Comput. 4 (1992) 772-780.
6. [6] J.A. Benediktsson, P.H. Swain and O.K. Ersoy, Neural network approaches versus statistical methods in classification of multisource remote sensing data, IEEE Trans. Geoscience and Remote Sensing 28 (4) (1990) 540-552.
7. [7] H. Bischof, W. Schneider and A.J. Pinz, Multispectral classification of Landsat-images using neural networks, IEEE Trans. Geoscience and Remote Sensing 30 (3) (1992) 482-490.
8. [8] D. Black, The Theory of Committees and Elections (Cambridge University Press, London, 1993).
9. [9] A.C. Bovik, M. Clark and W. Geisler, Multichannel texture analysis using localized spatial filters, IEEE Trans. PAMI 12(1) (1990) 55-73.
10. [10] M. Ceccarelli, A. Farina, A. Petrosino, R. Vaccaro and F. Vinelli, SAR image segmentation using textural information and neural classifiers, L'Onde Electrique 74 (3) (1994) 24-28.
11. [11] S.B. Cho and J. Kim, Feedforward neural network architectures for complex classification problems, in: Proc. 2nd Internat. Conf. on Fuzzy Logic & Neural Networks, Iizuka, 1992.
12. [12] G. Cybenko, Approximation by superposition of sigmoidal functions, Math. Control, Signal and Systems 2 (1989) 303-314.
13. [13] J.G. Daugman, Uncertainty relation for resolution in space spatial-frequency, and orientation optimized by two-dimensional visual cortical filters. J. OSA 2 (7) (1985) 1160-1169.
14. [14] S.E. Decatur, Applications of neural networks to terrain classification, in: Proc. IJCNN 1990, Washington, DC, 283-288, (Lawrence Erlbaum, London, 1990).
15. [15] P.A. Devijver and J. Kittler, Pattern Recognition: A Statistical Approach (Prentice-Hall, London, 1982).
16. [16] A.K. Jain and F. Farrokhnia, Unsupervised texture segmentation using Gabor filters, Pattern Recognition 24 (1991) 1167-1186.
17. [17] C. Genest and J.V. Zidek, Combining probability distributions: A critique and an annotated bibliography, Statist. Sci. 1 (1) (1986) 114-148.
18. [18] P.E. Gill and W. Murray, Safeguarded steplenght algorithms for optimization using descent methods, NPL Report 37, National Physical Laboratory, Division of Numerical Analysis and Computing, Middlesex, UK.
19. [19] E.B. Hall, A.E. Wessel and G.L. Wise, Some aspects of fusion in estimation theory, IEEE Trans. Inform. Theory 37 (2) (1991) 420-422.
20. [20] L.K. Hansen and P. Salamon, Neural network ensembles, IEEE Trans. Pattern Analysis and Machine Intelligence 12 (10) (1990) 993-1001.
21. [21] P.D. Heermann and N. Khazenie, Classification of multispectral remote sensing data using a back-propagation neural network, IEEE Trans. Geoscience and Remote Sensing 30 (1) (1992) 81-88.
22. [22] R.A. Jacobs, M.I. Jordan, S.J. Nowlan and G.E. Hinton, Adaptive mixtures of local experts, Neural Comput. 3 (2) (1991).
23. [23] A.K. Jain, Fundation of Digital Image Processing (Prentice-Hall, Englewood Cliffs, NJ, 1989).
24. [24] T. Kohonen, The self-organizing map, Proc. IEEE 78 (9) (1990) 1464-1479.
25. [25] R. Krishnapuram and J. Lee, Fuzzy-set-based hierarchical networks for information fusion in computer vision, Neural Networks 5 (2) (1992) 335-350.
26. [26] J. Lee, R.C. Weger, S.K. Sengupta and R.M. Welch, A neural network approach to cloud classification, IEEE Trans. Geoscience and Remote Sensing 28 (5) (1990) 846-855.
27. [27] M.D. Richard and R.P. Lippmann, Neural network classifiers estimate Bayesian a posteriori probabilities, Neural Comput. 3 (1991) 461-483.
28. [28] S. Mallat, A theory for multiresolution signal decomposition: The wavelet representation, IEEE Trans. PAMI 11 (7) (1989).
29. [29] G. Mani, Lowering variance of decisions by using artificial neural networks portfolios, Neural Comput. 3 (1991) 484-486.
30. [30] J. Orlando, R. Mann and S. Haykin, Classification of sea-ice images using a dual-polarized radar, IEEE J. Oceanic Engineering 15 (3) (1990) 228-234.
31. [31] M. Perrone, Improving regression estimation: Averaging methods for variance reduction with extensions to general convex measure optimization, Ph.D. Thesis, Dept. of Physics, Brown University, (1993).
32. [32] M.J.D. Powell, Restart procedures for the conjugate gradient method, Math. Programming 12 (1977) 241-254.
33. [33] D. Rumelhart D., G. Hinton and G. Williams, Learning internal representation by error propagation, in: D. Rumelhart and F. McClelland, eds., Parallel Distributed Processing, Vol. 1 (MIT Press, Cambridge, MA, 1986).
34. [34] C. Shang and K. Brown, Principal features-based texture classification with neural networks, Pattern Recognition 27 (5) (1994) 675-687.
35. [35] L. Xu, A. Krzyzak and C.Y. Suen, Methods of combining multiple classifiers and their applications to handwriting recognition, IEEE Trans. Systems, Man and Cybernetics 22 (3) (1992) 418-435.
36. [36] B. Widrow and M. Hoff, Adaptive switching circuits, in: 1960 IRE WESCON Convention Record 4 (IRE, New York, 1960) 96-104.
37. [37] D.H. Wolpert, Stacked Generalization, Tech. Rept. LA-UR-90-3460, Los Alamos National Laboratory, NM, 1990.