Abstract
Optical remote sensing (RS) images captured in different conditions might exhibit nonlinear changes. The registration of theses image is an important process. In this paper, we evaluate the performance of the three most successful state-of-the-art descriptors in a feature-based registration process. We have separated the detector from the descriptor as their performance depends on the position of the detected features. The descriptors are compared according to their Recall and runtime efficiency and these deals with several geometric and photometric changes. We also proposed an optimization to the SURF algorithm for color images, called O-SURF, which is a combination of the MSER detector and the SURF descriptor. The results show the effectiveness of proposed improvements compared to base SURF version. Finally, based on the test results, we propose an approach to register automatically optical RS images with subpixel accuracy.
Similar content being viewed by others
References
Toutin, T.: Geometric processing of remote sensing images: models, algorithms and methods. Int. J. Remote Sens. 25(10), 1893–1924 (2004)
Goshtasby, A.A.: 2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications. Wiley Press, London (2005)
Lowe, D.G.: Object recognition from local scale-invariant features. In: International Conference on Computer Vision ICCV, Corfu, Greece, pp. 1150–1157 (1999)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
Bay, H., Ess, A., Tuytelaars, T., Vangool, L.: Speeded-up robust features (surf). Comput. Vis. Image Underst. 110(3), 346–359 (2008)
Bouchiha, R., Besbes, K.: Comparative study of interest point detectors and descriptors for automatic remote-sensing image registration. Int. Rev. Comput. Softw. 5(3), 264–275 (2010)
Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. British Mach. Vis. Conf. 1, 384–393 (2002)
Ke, Y., Sukthankar, R.: Pca-sift: a more distinctive representation for local image descriptors. IEEE Comput. Soci. Conf. Comput. Vis. Pattern Recognit. 2, 506–513 (2004)
Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Van Gool, L.: A comparison of affine region detectors. Int. J. Comput. Vis. 65(1/2), 43–72 (2005)
Beis, J., S., Lowe, D., G.: Shape indexing using approximate nearest-neighbour search in high-dimensional spaces. In: Conference on Computer Vision and Pattern Recognition (CVPR 97), Washington, DC, USA, pp. 1000–1006 (1997)
Lowe, D.: Distinctive image features from scale invariant keypoints. In. International Journal of Computer Vision 60(2), 91–110 (2004)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bouchiha, R., Besbes, K. Comparison of local descriptors for automatic remote sensing image registration. SIViP 9, 463–469 (2015). https://doi.org/10.1007/s11760-013-0460-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11760-013-0460-3