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Original Articles

APPROCHE MULTIPOLARISATION ET TEXTURALE POUR LA RECONNAISSANCE DES CULTURES À L'AIDE DE DONNÉES RADAR AÉROPORTÉ

Pages 138-157 | Published online: 01 Aug 2014

Références

  • Anys, H., D.-C. He, L. Wang et Q.H.J. Gwyn. 1994. «Classification d'images radar aéroporté multipolarisations en milieu agricole», International Journal of Remote Sensing (accepté).
  • Ban, Y., P.M. Treitz, and P.J. Howarth. 1993. “Improving the Accuracy of Synthetic Aperture Radar for Agricultural Crop Classification,” Proceedings, 16th Canadian Symposium on Remote Sensing, Sherbrooke (Québec), Canada, June 7–10, pp. 367–370.
  • Boivin, F., Q.H.J. Gwyn et K.P.B. Thomson. 1990. «Effets de la géométrie de surface de champs de maïs sur la rétrodiffusion du radar bande C», Canadian Journal of Remote Sensing, 16:16–28.
  • Brisco, B., R.J. Brown, and M.J. Manore. 1989. “Early Season Crop Discrimination with Combined SAR and TM Data,” Canadian Journal of Remote Sensing, 15:44–54.
  • Brown, R.J., M.J. Manore, and S. Poirier. 1992. ” Correlation Between X-, C-, and L-Band Imagery Within an Agricultural Environment,” International Journal of Remote Sensing, Vol. 13, No. 9, pp. 1645–1661.
  • Cruse, D., C.J. Oddy, and A. Wright. 1984. “A Segmented Image Data Base (SID) for Image Analysis,” 7th International Conference on Pattern Recognition, IEEE, pp. 493–496.
  • Duda, R.O. and P.E. Hart. 1973. Pattern Classification and Scene Analysis. New York: Wiley.
  • Fischer, J.A., R.J. Brown, and B. Brisco. 1992. “The Effects of Changes in Soil Moisture and Rainfall on SAR Data Crop Classification,” Proceedings, 15th Canadian Symposium on Remote Sensing, Toronto (Ontario), Canada, June 1–4, pp. 221–226.
  • Franklin, S.E. and R.D. Peddle. 1989. “Spectral Texture for Improved Class Discrimination in Complex Terrain,” International Journal of Remote Sensing, 10:1437–1443.
  • Gong, P. 1990. Improving Accuracies in Land-Use Classification with High Spatial Resolution Satellite Data: A Contextual Classification Approach, Ph.D. thesis, University of Waterloo, Waterloo, Ontario, Canada, 181 pp.
  • Haralick, R.M. 1979. “Statistical and Structural Approaches to Texture,” Proceedings of the IEEE, Vol. 67, No. 5, pp. 786–804.
  • Haralick, R.M., K. Shanmugam, and D. Its'hak. 1973. “Textural Features for Image Classification,” IEEE Transactions on Systems, Man and Cybernetics, SMC-3:610–621.
  • Hess, L.L., J.M. Melack, and F.W. Davis. 1994. “Mapping of Floodplain Inundation with Multifrequency Polarimetric SAR: Use of a Tree-Based Model”, IGARSS 1994, Institute of Technology, Pasadena, California, Vol. II, pp. 1072–1073.
  • Hevenor, R.A. 1985. Third-Order Co-occurrence Texture Analysis Applied to Samples of High Resolution Synthetic Aperture Radar Imagery, U.S. Army Corps of Engineers. Engineering Topographic Laboratories, Fort Belvoir, Virginia 22060–5546, 32 pp.
  • Kailath, T. 1967. “The Divergence and Battacharyya Distance Measures in Signal Selection,” IEEE Transactions on Communication Technology, COM-15:52–60.
  • Kilpelä, E. and J. Heikilä. 1990. “Comparison of Some Texture Classifiers,” Proceedings, Symposium on Global and Environmental Monitoring Techniques and Impact, Sept. 17–21, Victoria, British Columbia, Canada, Vol. 28, part 7.2, pp. 333–339.
  • Lee, J.H. and D.W. Philpot. 1991. “Spectral Texture Pattern Matching: A Classifier for Digital Imagery, IEEE Transactions on Geoscience and Remote Sensing, Vol. 29, No. 4, pp. 545–554.
  • Laur, H. 1989. Analyse d'images radar en télédétection : Discriminateurs radiométriques et texturaux, Thèse de doctorat, Université Paul Sabatier, No. 403, Toulouse, 244 p.
  • Laur, H., T. Le Toan, and A. Lopes. 1987. “Textural Segmentation of SAR Images Using First Order Statistical Parameters,” Proceedings, IGARSS 1987 Symposium, Ann Arbor, Michigan, May 18–21, pp. 1463–1468.
  • Marceau, D., P.J. Howarth, J.M. Dubois, and D.J. Gratton. 1990. “Evaluation of the Grey-Level Cooccurrence Method for Land-Cover Classification Using SPOT Imagery,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 28, No. 4, pp. 513–519.
  • PCI Inc. 1991. EASI/PACE Image Processing Manual, Version 5.0, Perceptron Computing Inc, Richmond Hill, Ontario.
  • Peddle, R.D. 1992. “A Comparison of Landcover Classification by Maximum Likelihood Linear Discriminant Analysis and Evidential Reasoning,” Proceedings, 15th Canadian Symposium on Remote Sensing, June 1–4, Toronto, Ontario, Canada, pp. 419–422.
  • Poirier, S., K.P.B. Thomson, and R.J. Brown. 1986. «Comparaison des données ROS en bande C, selon deux angles de dépression différents pour le domaine agricole», Proceedings, 10th Canadian Symposium on Remote Sensing, Edmonton, Alberta. Ottawa: Canadian Aeronautics and Space Institute, pp. 185–189.
  • Pratt, W.K. 1991. Digital Image Processing (2nd ed.). New York: Wiley, 698 pp.
  • Pultz, T.J., and R.J. Brown. 1987. “SAR Image Classification of Agricultural Targets Using First- and Second-Order Statistics,” Canadian Journal of Remote Sensing, 13:85–91.
  • Richards, J.A. 1986. Remote Sensing Digital Image Analysis: An Introduction. New York: Springer-Verlag Berlin Heidelberg.
  • Sali, E. and H. Wolfson. 1992. “Texture Classification in Aerial Photographs and Satellite Data,” International Journal of Remote Sensing, 13:3395–3408.
  • Salvaggio, C., D.J. Robert, and J.R. Schott. 1990. Generation of Textural Features From Monochromatic Imagery for Land Cover Classification. Rochester Institute of Technology, RIT/DIRS Report #89/90–63–130.
  • Slimani, M. 1986. Analyse de texture en télédétection : Application à la segmentation d'images satellites à haute résolution type Spot, Thèse de doctorat, Université de Rennes I, 82 p.
  • Sun, C. and W.G. Wee. 1983. “Neighboring Grey Level Dependence Matrix for Texture Classification,” Computer Vision, Graphics and Image Processing, 23:341–352.
  • Swain, P.H. and S.M. Davis. 1978. Remote Sensing: The Quantitative Approach. New York: McGraw-Hill.
  • Swain P.H. and R.C. King. 1973. “Two Effective Feature Selection Criteria for Multispectral Remote Sensing,” Proceedings, 1st International Joint Conference on Pattern Recognition, November, pp. 536–540.
  • Swain, P.H., T.V. Robertson, and A.G. Wacker. 1971. Comparison of Divergence and B-Distance in Feature Selection. Information Note 020871, Laboratory for Applications of Remote Sensing, Purdue University, West Lafayette, Indiana, 12 pp.
  • Thomson, K.P.B., A. Jaton, G. Edwards, J. Pouliot et A. Touré. 1992. «Analyse des données ROS multibande et multipolarisation en milieu agricole, Proceedings, 15th Canadian Symposium on Remote Sensing, Toronto (Ontario), Canada, June 1–4, pp. 227–232.
  • Treitz, P.M. and J.P. Howarth. 1993. “Classification of Agricultural Crops Using SAR Tone and Texture Statistics,” Proceedings, 16th Canadian Symposium on Remote Sensing, Sherbrooke (Québec), Canada, June 7–10, pp. 343–347.
  • Ulaby, F.T., F. Kouyate, and B. Brisco. 1986. “Textural Information in SAR Images,” IEEE Transactions on Geoscience and Remote Sensing, GE-24:235–245.
  • Unser, M. 1986. “Local Linear Transforms for Texture Measurements,” Signal Processing, 11:61–79.
  • Van Leeuwen, H.J.C., J.G.P.W. Clevers, and G.J. Rijckenberg. 1994. “Synergistic Use of Optical and Microwave Remote Sensing Data Using Models and Specific Features with Respect to the Sugar Beet Crop,” IGARSS 1994, California Institute of Technology, Pasadena, California, Vol. II, pp. 827–831.
  • Vickers, A.L. and J.W. Modestino. 1982. “A Maximum Likelihood Approach to Texture Classification,” IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-4:61–68.
  • Wacker, A.G. 1971. The Minimum Distance Approach to Classification, Ph.D. thesis, Purdue University, West Lafayette.
  • Wang, L. 1994. «Un nouvel espace de texture», International Journal of Remote Sensing, 15, pp. 1713–1723.
  • Wang, L. and D.-C. He. 1990. “A New Statistical Approach for Texture Analysis,” Photogrammetric Engineering and Remote Sensing, 56:61–66.
  • Wang, L. et D.-C. He. 1991. «Un nouvel algorithme de classification non dirigée», International Journal of Remote Sensing, 12, pp. 2439–2444.

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