The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
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(a) Original image ©ONES 
(b) Sub-image classification 
vmsMm 
(c) Ground truth ©Google Maps 
Figure 4: Large image indexing 
ACKNOWLEDGEMENTS 
This work was partially funded by the French Space Agency 
(CNES), ACI QuerySat, the STIC INRIA-Tunisia programme, 
and EU NoE Muscle (FP6-507752). The data was kindly 
provided by CNES and by Sup’com, Tunis. The first author 
would like to thank INRIA for the PhD fellowship. 
REFERENCES 
Bhattacharya, A., Jermyn, I. H., Descombes, X. and Zerubia, J., 
2006. Computing statistics from a graph representation of road 
networks in satellite images for indexing and retrieval. In: Proc. 
CompIMAGE - Computational Modelling of Objects 
Represented in Images: Fundamentals, Methods and 
Applications, Coimbra, Portugal. 
Bhattacharya, A., Roux, M., Maitre, H., Jermyn, I. FT, 
Descombes, X. and Zerubia, J., 2007. Indexing satellite images 
with features computed from man-made structures on the 
earth’s surface. In: Proc. International Workshop on Content- 
Based Multimedia Indexing, pp. 244-250. 
Cormen, T., Leiserson, C., Rivest, R. and Stein, C., 2001. 
Introduction to Algorithms. MIT Press and McGraw-Hill. 
Daschiel, H. and Datcu,M., 2005. Image information mining 
system evaluation using information-theoretic measures. 
EURASIP Journal on Applied Signal Processing 2005(14), pp. 
2153-2163. 
Desolneux, A., Maison, L. and Morel, J.-M., 2000. 
Meaningfulalignments. International Journal of Computer 
Vision 40(1), pp. 7-23. 
Dimitrov, P., Phillips, C. and Siddiqi, K., 2000. Robust and 
efficient skeletal graphs. In: Proc. IEEE Computer Vision and 
Pattern Recognition (CVPR), Hilton Head Island, USA, pp. 
1417-1423. 
Duda, R., Hart, P. and Stork, D., 2000. Pattern Classification, 
2ed. Wiley-Interscience. 
Fischler, M., Tenenbaum, J. and Wolf, H., 1981. Detection of 
roads and linear structures in low-resolution aerial imagery 
using a multisource knowledge integration technique. Computer 
Graphics and Image Processing 15(3), pp. 201-223. 
Khatir, L., 1989. Recherche d’algorithmes de localisation de 
routes dans les images satellite 'a haute resolution. Application 
'a l’imagerie SPOT. PhD thesis, Universife Paul Sabatier de 
Toulouse, France. 
Lacoste, C., Descombes, X. and Zerubia, J., 2005. Point 
processes for unsupervised line network extraction in remote 
sensing. IEEE Trans. Pattern Analysis and Machine Intelligence 
27(10), pp. 1568-1579. 
Lowe, D., 2004. Distinctive image features from scale-invariant 
keypoints. International Journal of Computer Vision 60(2), pp. 
91-110. 
Maître, H., 2007. Indexing and retrieval in large satellite image 
databases. In: Proc. 5th Int. Symp. Multispectral Image 
Processing and Pattern Recognition (MIPPR). 
Platt, J., 1999. Probabilities for support vector machines. In: A. 
Smola, P. Bartlett, B. Schlkopf and D. Schuurmans (eds), 
Advances in Large Margin Classifiers, MIT Press, pp. 61-74. 
Rochery, M., Jermyn, I. H. and Zerubia, J., 2003. Higher order 
active contours and their application to the detection of line 
networks in satellite imagery. In: Proc. IEEEWorkshop 
Variational, Geometric and Level Set Methods in Computer 
Vision, at ICCV, Nice, France. 
Roux, M., 1992. Recalage d’images multi-sources. Application 
au recalage d’une image SPOT et d’une carte. PhD thesis, 
Ecole National Supérieure des Télécommunications, Paris, 
France. 
Schroeder, M., Rehrauer, H., Seidel, K. and Datcu, M., 1998. 
Spatial information retrieval from remote sensing images: Part 
ill Gibbs Markov random fields. IEEE Trans. Geoscience and 
Remote Sensing 36, pp. 1446-1455. 
Serendero, M., 1989. Extraction d’informations symboliques en 
imagerie SPOT: r'eseaux de communication et agglomérations. 
PhD thesis, Université de Nice, France. 
Siddiqi, K., Bouix, S., Tannenbaum, A. and Zucker, S. W., 
2002. Hamilton-jacobi skeleton. International Journal of 
Computer Vision 48(3), pp. 215-231.