Abstract
Detection and matching of features from satellite images taken from different sensors, viewpoints, or at different times are important tasks when manipulating and processing remote sensing data for many applications. This paper presents a scheme for satellite image co-registration using invariant local features. Different corner and scale based feature detectors have been tested during the keypoint extraction, descriptor construction and matching processes. The framework suggests a sub-sampling process which controls the number of extracted key points for a real time processing and for minimizing the hardware requirements. After getting the pairwise matches between the input images, a full registration process is followed by applying bundle adjustment and image warping then compositing the registered version. Harris and GFTT have recorded good results with ASTER images while both with SURF give the most stable performance on optical images in terms of better inliers ratios and running time compared to the other detectors. SIFT detector has recorded the best inliers ratios on TerraSAR-X data while it still has a weak performance with other optical images like Rapid-Eye and ASTER.
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References
Agrawal, M., Konolige, K., Blas, M.R.: Censure: Center surround extremas for realtime feature detection and matching. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 102–115. Springer, Heidelberg (2008)
Bay, H., Tuytelaars, T., Van Gool, L.: Surf: Speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part I. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Bouchiha, R., Besbes, K.: Automatic remote-sensing image registration using surf. International Journal of Computer Theory and Engineering 5(1), 88–92 (2013)
Calonder, M., Lepetit, V., Strecha, C., Fua, P.: Brief: Binary robust independent elementary features. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 778–792. Springer, Heidelberg (2010)
Harris, C., Stephens, M.: A combined corner and edge detector. In: Proceedings of the 4th Alvey Vision Conference, pp. 147–151 (1988)
Hong, T.D., Schowengerdt, R.A.: A robust technique for precise registration of radar and optical satellite images. Photogrammetric Engineering and Remote Sensing 71(5), 585–594 (2005)
Juan, L., Gwon, O.: A comparison of sift, pca-sift and surf. International Journal of Image Processing (IJIP) 3(4), 143–152 (2009)
Khan, N.Y., McCane, B., Wyvill, G.: SIFT and SURF performance evaluation against various image deformations on benchmark dataset. In: Bradley, A.P., Jackway, P.T. (eds.) DICTA, pp. 501–506. IEEE (2011)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Gool, L.: A comparison of affine region detectors. International Journal of Computer Vision 65(1-2), 43–72 (2005)
Moravec, H.: Obstacle avoidance and navigation in the real world by a seeing robot rover. Tech Report CMU-RI-TR-3 Carnegie-Mellon University, Robotics Institute (1980)
Rosten, E., Drummond, T.W.: Machine learning for high speed corner detection. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part I. LNCS, vol. 3951, pp. 430–443. Springer, Heidelberg (2006)
Schmidt, A., Kraft, M., Kasiński, A.: An evaluation of image feature detectors and descriptors for robot navigation. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2010, Part II. LNCS, vol. 6375, pp. 251–259. Springer, Heidelberg (2010)
Shi, J., Tomasi, C.: Good features to track. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600 (June 1994)
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Tahoun, M., El Rahman Shabayek, A., Reulke, R., Hassanien, A.E. (2015). Co-registration of Satellite Images Based on Invariant Local Features. In: Filev, D., et al. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-319-11310-4_56
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DOI: https://doi.org/10.1007/978-3-319-11310-4_56
Publisher Name: Springer, Cham
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