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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
Clausi D A. and Yue, B., 2004. Texture Segmentation 
Comparison Using Grey Level Co-occurrence Probabilities and 
Markov Random Fields, Proceedings of the 17th International 
Conference on Pattern Recognition (ICPR’04); Available at: 
nttp://ieeexplore.ieee.org/stamp/. 
Chellappa, R. and Chatterjee, S., 1985. Classification of 
Textures Using Gaussian Markov Random Fields, IEEE 
Transactions on Acoustics, Speech, and Signal Processing, 33, 
pp. 959-963. 
Chen, C H., Pau, L F. and Wang, P S P., 1998. The Handbook 
of Pattern Recognition and Computer Vision (2nd Edition), by 
World Scientific Publishing Co., pp. 207-248. 
Dong, Y., Milne, A. K., and Forster, B. C., 2001. Segmentation 
and classification of vegetated areas using polarimetric SAR 
image data, JEEE Trans Geosci. Remote Sens., 39 (2), pp. 321- 
329. 
Hartigan, J.. A, and Wong, M. A. 1979. A K-means 
clustering algorithm; Appl. Stat.. 28(1), pp. 100-108. 
Haralick, R..M., Shanmugan, K., and Dinstein, 1.1973. 
Textural features for image classification, IEEE Transactions 
on systems, Man, and cybernetics, 3 (6), pp. 610-621. 
Jain, A. K., Murty, M. N., Flynn, P. J., 1999. Data clustering: a 
review, ACM Computing Surveys, 31(3), pp. 264-323. 
Kohei, A., and XianQiang, Bu., 2007. ISODATA clustering 
with parameter (threshold for merge and split) estimation based 
on GA: Genetic Algorithm, Report Facalty Science 
Engineering, Saga University, 36 (1), pp. 17-23 ( available at 
http:/dlwww.dl.saga- 
uac.jp/contents/mgzn/ZR00005459/ZR00005459.pdf as on 
January 17, 2011). 
Lucieer, A., Stein A., and Fisher, P., 2005. 'Texture-based 
segmentation of high-resolution remotely sensed imagery for 
identification of fuzzy objects', International Journal of Remote 
Sensing, 26(14), pp. 2917-2936 
Oliver, C. J., and Quegan, S., 1998. Understanding Synthetic 
Aperture Radar Images, New York: Artech House. 
Ojala, T.P.M., Harwood, D., 1996. A comparative study of 
texture measures with classification based on featured 
distribution. Pattern Recognition, 29(1), pp. 51-59. 
Ojala, T., Pietikäinen, M., and Mäenpää, T., 2002. 
Multiresolution gray-scale and rotation invariant texture 
classification with local binary patterns. IEEE Transactions on 
Pattern Analysis and Machine Intelligence, 24, pp. 971-987. 
Petrou, M., Giorgini, F., and Smits, P., 2002. Modelling the 
histograms of various classes in SAR images, Pattern Recognit. 
Lett., 23(9), pp. 1103-1107. 
Richards, J. A., 1995. Remote Sensing Digital Image 
Analysis: An Introduction, Springer-Verlag, pp. 265-290 
Szira yi, T., Zerubia, J., Czul, L., Geldreich, D. and Kato, Z., 
2000. Image Segmentation Using Markov Random Field Model 
in Fully Parallel Cellular Network Architectures, Real-Time 
Imaging, 6, pp. 195-211. 
Solberg, A. H. S. S., and Jain, A. K., 1996. A Markov Random 
Field Model for Classification of Multisource Satellite Imagery, 
IEEE Transactions On Geoscience And Remote Sensing, 34(1). 
Tsai, F. and Chou M J., 2006. Texture Augmented Analysis Of 
High Resolution Satellite Imagery In Detecting Invasive Plant 
Species, Journal of the Chinese Institute of Engineers, 29(4), 
pp. 581-592. 
Tsai, F., Chou, M. J. and Wang, H. H., 2005. Texture Analysis 
of High Resolution Satellite Imagery for Mapping Invasive 
Plants, IEEE International Geoscience and Remote Sensing 
Symposium Proceedings, 4, pp. 3024- 3027. 
Tison, C., Nicolas, J. M., Tupin, F., and Maitre, H., 2004. A 
new statistical model for Markovian classification of urban 
areas in high-resolution SAR images, IEEE Trans. Geosci. 
Remote Sens., 42(10), pp. 2046-2057.