Application of Neural Networks to Radar Image Classification

IEEE Transactions on Geoscience and Remote Sensing

Volumn 32, Issue 1, 1994, Pages 100-109

  Hara, Yoshihisa ^a   Atkins, Robert G ^a   Shin, Robert T ^a   Kong, J A ^a   Yueh, Simon H ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MITSUBISHI ELECTRIC CORPORATION   (Japan)

^c CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); IMAGE ANALYSIS; ITERATIVE METHODS; NEURAL NETWORKS; POLARIMETERS; REMOTE SENSING; SYNTHETIC APERTURE RADAR;

LEARNING VECTOR QUANTIZATION (LVQ); MAXIMUM LIKELIHOOD (ML) CLASSIFIER; TERRAIN COVER CLASSIFICATION;

RADAR IMAGING;

EID: 0027963979     PISSN: 01962892     EISSN: 15580644     Source Type: Journal    
DOI: 10.1109/36.285193     Document Type: Article

References (18)

1. A. G. Wacker and D. A. Landgrebe, “Minimum distance classification in remote sensing,” in Proc. 1st Canad. Symp. Remote Sens., Ottawa, 1972.
2. P. H. Swain and S. M. Davis, Eds., Remote Sensing: The Quantitative Approach. New York: McGraw-Hill, 1978.
3. J. J. van Zyl, “Unsupervised classification of scattering behavior using radar polarimetry data,” IEEE Trans. Geosci. Remote Sens., vol. 27, pp. 36–45, 1989.
4. H. H. Lim, A.A. Swartz, H.A. Yueh, J.A. Kong, R.T. Shin, J. J. van Zyl, “Classification of earth terrain using polarimetric synthetic aperture radar images,” J. Geophys. Res., vol. 94, no. B6, pp. 7049–7057, June 1989.
5. P. D. Herman and N. Khazenie, “Classification of multispectral remote sensing data using a back-propagation neural network,” IEEE Trans. Geosci. Remote Sens., vol. 30, pp. 81–88, Jan. 1992.
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. Geosci. Remote Sens., vol. 28, pp. 540–552, July 1990.
7. S. E. Decatur, “Applications of neural networks to terrain classification,” M.S. thesis, Dep. Elec. Eng. Comput. Sci., MIT, Cambridge, MA, June 1989.
8. R. G. Atkins, R. T. Shin, and J. A. Kong, “A neural network method for high range resolution target classification,” in Progress in Electromagnetics magnetics Research, Vol. 4. New York: Elsevier, 1990.
9. G. Vrckovnik, T. Chung, and C. R. Carter, “Classifying impulse response radar waveforms using principal components analysis and neural networks,” in Proc. Int. Joint Conf Neural Networks, San Diego, CA, June 17–21, 1990, pp. 45–50.
10. D. S. Levine and P. Andrew Penz, “ART 1.5--A simplified adaptive resonance network for classifying low-dimensional analog data,” in Proc. Int. Joint Conf. Neural Networks, Washington, DC, Jan. 15–19, 1990, pp. 639–642.
11. J. A. Kong, A.A. Swartz, H.A. Yueh, L.M. Novak and R. T. Shin, “Identification of terrain cover using the optimum polarimetric classifier,” J. Eiectromagn. Waves Appl., vol. 2, no. 2, pp. 171–194, 1988
12. H. A. Yueh, A.A. Swartz, J.A. Kong, R.T. Shin and L. M. Novak, “Bayes classification of terrain cover using normalized polarimetric data,” J. Geophys. Res., vol. 93, no. B12, pp. 15261–15267, Dec. 1988.
13. J. A. Richards, Remote Sensing Digital Image Analysis: An Introduction. Berlin: Springer-Verlag, 1986.
14. J. A. Hartigan, Clustering Algorithm. New York: John Wiley & Sons, 1975.
15. G. A, Carpenter and S. A. Grossberg, “ART2: Self-organization of stable category recognition codes for analog input patterns,” Appl. Opt., Special Issue Neural Networks, 1987.
16. G. A. Carpenter and S. A. Grossberg, “The ART of adaptive pattern recognition by self-organizing neural network,” IEEE Comput., vol. 21, pp. 77–88, Mar. 1988.
17. T. Kohonen, Self-Organization and Associative Memory. Berlin: Springer-Verlag, 1989.
18. L. Tsang, J. A. Kong, and R. T. Shin, Theory of Microwave Remote Sensing. New York: Wiley-Interscience, 1985.