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Supervised Classification Systems for High Resolution Satellite Images  

전영준 (동의대학교 컴퓨터공학과)
김진일 (동의대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.9, no.3, 2003 , pp. 301-310 More about this Journal
Abstract
In this paper, we design and Implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the m()st effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.
Keywords
고해상도 위성영상;감독분류;IKONOS 위성영상;
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  • Reference
1 John A. Richards, Remote Sensing Digital Image Analysis : An Introduction, Second, Revised and Enlarged Edition, pp. 229-262, Springer-Verlag, 1994
2 R. Schowengerdt, Techniques of Image Processing and Classification in Remote Sensing, 1st Ed., pp. 1-58, Academic Press, 1983
3 Jimenez L.O. and Landgrebe D.A., 'Supervised classification in high-dimensional space: geometrical, statistical, and asymptotical properties of multivariate data Systems,' Man, and Cybernetics, Part C, Applications and Reviews, IEEE Transactions on, Volume 28 Issue 1, pp. 39-54, 1998   DOI
4 Melgani, F., Hashemy B.A.R. and Taha S.M.R. 'An explicit fuzzy supervised classification method for multispectral remote sensing images,' Geoscience and Remote Sensing, IEEE Transactions on, Vol. 38 Issue 1 Part 1, pp. 287-295, 2000   DOI   ScienceOn
5 Saldju Tadjudin and David A. Landgrebe, 'Covariance Estimation For Limited Training Samples,' IEEE International Geoscience and Remote Sensing Symposium, Seattle, W A July 6-10, pp. 2688-2690, 1998   DOI
6 Hoffbeck, Joseph P. and David A. Landgrebe, 'Classification of Remote Sensing Images having High Spectral Resolution,' Remote Sensing of Environment, Vol. 57, No.3, pp, 119-126, September 1996   DOI   ScienceOn
7 Ishibushi, H., K.Nozaki and H.Tanaka, 'Distributed representation of fuzzy rules and its application to pattern classification,' Fuzzy Sets and Systems Vol. 52, pp. 21-32, 1992   DOI   ScienceOn
8 Nakashiim T., Nakai G. and Ishibuchi, H., 'Improving the performance of fuzzy classification systems by membership function learning and feature selection,' Fuzzy Systems, FUZZ-IEEE '02. Proceedings of the 2002 IEEE International Conference on, Vol. 1, pp. 488-493, 2002   DOI
9 Wang, F., 1990, 'Fuzzy Supervised Classification of Remote Sensing Images,' IEEE Trans. on Geosicience and Remote Sensing, Vol. 28, No. 2, pp. 194-201, 1990   DOI   ScienceOn
10 Gorte, B. and Stein, A, 'Bayesian classification and class area estimation of satellite images using stratification, ' Geoscience and Remote Sensing, IEEE Transactions on, Vol. 36 Issue 3, pp. 803-812, 1998   DOI   ScienceOn
11 Richard A Johnson, Dean W. Wichern, Applied Multivariate Statistical Analysis, Prentice Hall, pp. 573-627, 1992
12 David Landgrebe, Information Extraction Principles and Methods for Multispectral and Hyperspectral Image Data, Chapter 1 of Information Processing for Remote Sensing, edited by C. H. Chen, published by the World Scientific Publishing Co., Inc., pp. 1-30, Spring, 1999
13 Pierce L., Samples G., Dobson M.C. and Ulaby, F., 'An automated unsupervised/supervised classification methodology,' Geoscience and Remote Sensing Symposium Proceedings, IGARSS '98. 1998 IEEE International, Vol. 4, pp. 1781-1783, 1998   DOI
14 Jain, A.K., Duin, P.W. and Jianchang Mao, 'Statistical pattern recognition: a review,' Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 22 Issue 1, pp. 4-37, 2000   DOI   ScienceOn