The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
A Novel Coarse-to-Fine Scheme for Automatic Image Registration Based on SIFT and Mutual Information
Abstract
Automatic image registration is a vital yet challenging task, particularly for remote sensing images. A fully automatic registration approach which is accurate, robust, and fast is required. For this purpose, a novel coarse-to-fine scheme for automatic image registration is proposed in this paper. This scheme consists of a preregistration process (coarse registration) and a fine-tuning process (fine registration). To begin with, the preregistration process is implemented by the scale-invariant feature transform approach equipped with a reliable outlier removal procedure. The coarse results provide a near-optimal initial solution for the optimizer in the fine-tuning process. Next, the fine-tuning process is implemented by the maximization of mutual information using a modified Marquardt-Levenberg search strategy in a multiresolution framework. The proposed algorithm is tested on various remote sensing optical and synthetic aperture radar images taken at different situations (multispectral, multisensor, and multitemporal) with the affine transformation model. The experimental results demonstrate the accuracy, robustness, and efficiency of the proposed algorithm.
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Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
A performance evaluation of local descriptors
Mikolajczyk, K., & Schmid, C. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.188 · Cited by 6,723
Multimodality image registration by maximization of mutual information
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., & Suetens, P. (1997) · IEEE Transactions on Medical Imaging · doi:10.1109/42.563664 · Cited by 4,547
Cited by
Deep learning in medical image registration: a review
Fu, Y., Lei, Y., Wang, T., Curran, W. J., Liu, T., & Yang, X. (2020) · Physics in Medicine & Biology · doi:10.1088/1361-6560/ab843e · Cited by 661
Liu, J., Gong, M., Qin, K., & Zhang, P. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2636227 · Cited by 522
Self-citationRemote Sensing Image Registration With Modified SIFT and Enhanced Feature Matching
Ma, W., Wen, Z., Wu, Y., Jiao, L., Gong, M., Zheng, Y., & Liu, L. (2017) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2016.2600858 · Cited by 389
Self-citationA deep learning framework for remote sensing image registration
Wang, S., Quan, D., Liang, X., Ning, M., Guo, Y., & Jiao, L. (2018) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2017.12.012 · Cited by 292
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Metadata
- Authors
- Gong, M., Zhao, S., Jiao, L., Tian, D., & Wang, S.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2014-07
- Volume
- 52
- Issue
- 7
- Pages
- 4328-4338
- ISSN
- 0196-2892 (ISSN-L)
- 1558-0644
- OpenAlex
- W1972731536
- Cited by
- 301
- References
- 4
- FWCI
- 26.40
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gong, M., Zhao, S., Jiao, L., Tian, D., & Wang, S. (2014). A Novel Coarse-to-Fine Scheme for Automatic Image Registration Based on SIFT and Mutual Information. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/tgrs.2013.2281391
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