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http://dx.doi.org/10.7780/kjrs.2014.30.6.9

Image registration using outlier removal and triangulation-based local transformation  

Ye, Chul-Soo (Department of Ubiquitous IT, Far East University)
Publication Information
Korean Journal of Remote Sensing / v.30, no.6, 2014 , pp. 787-795 More about this Journal
Abstract
This paper presents an image registration using Triangulation-based Local Transformation (TLT) applied to the remaining matched points after elimination of the matched points with gross error. The corners extracted using geometric mean-based corner detector are matched using Pearson's correlation coefficient and then accepted as initial matched points only when they satisfy the Left-Right Consistency (LRC) check. We finally accept the remaining matched points whose RANdom SAmple Consensus (RANSAC)-based global transformation (RGT) errors are smaller than a predefined outlier threshold. After Delaunay triangulated irregular networks (TINs) are created using the final matched points on reference and sensed images, respectively, affine transformation is applied to every corresponding triangle and then all the inner pixels of the triangles on the sensed image are transformed to the reference image coordinate. The proposed algorithm was tested using KOMPSAT-2 images and the results showed higher image registration accuracy than the RANSAC-based global transformation.
Keywords
interest points; image registration; outlier removal; Pearson's correlation coefficient; triangulation-based local transformation;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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1 Althof, R.J., M.G.J. Wind, and J.T. Dobbins, 1997. A rapid and automatic image registration algorithm with subpixel accuracy, IEEE Transactions on Medical Imaging, 16(3): 308-316.   DOI
2 Castro, E.D. and C. Morandi, 1987. Registration of translated and rotated images using finite Fourier transform, IEEE Transactions on Pattern Analysis and Machine Intelligence, 9(5): 700-703.
3 Han, Y.K., D.J. Kim, and Y.I. Kim, 2011. Registration between high-resolution optical and SAR images using linear features, Korean Journal of Remote Sensing, 27(2): 141-150 (in Korean with English absract).   과학기술학회마을   DOI
4 Kanade T. and M. Okutomi, 1994. A stereo matching algorithm with an adaptive window: theory and experiment, IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(9): 920-932.   DOI   ScienceOn
5 Lowe, D.G., 2004. Distinctive image features from scale-Invariant keypoints, International Journal of Computer Vision, 60(2): 91-110.   DOI   ScienceOn
6 Suri, S. and P. Reinartz, 2010. Mutual-information based registration of TerraSAR-X and ikonos imagery in urban areas, IEEE Transactions on Geoscience and Remote Sensing, 48(2): 939-949.   DOI   ScienceOn
7 Viola, P. and W.M. Wells, 1997. Alignment by maximization of mutual information, International Journal of Computer Vision, 24(2): 137-154.   DOI   ScienceOn
8 Ye, C.S., C.G. Moon, and J.H. Jeon, 2006. Stereo matching method using directional feature vector, Journal of Control, Automation, and Systems Engineering, 13(1): 152-57.
9 Ye, C.S., 2011. Similarity measurement using Gabor energy feature and mutual information for image registration, Korean Journal of Remote Sensing, 27(6): 693-701.   과학기술학회마을   DOI
10 Ye, C.S., 2014a. Mutual information-based circular template matching for image registration, Korean Journal of Remote Sensing, 30(5): 547-557 (in Korean with English absract).   과학기술학회마을   DOI
11 Ye, C.S., 2014b. Corner detection based on geometric mean of eigenvalues, Proc. of 2014 KSRS Conference, Jeju, Korea, Oct. 16-17, pp.190-193.
12 Ye, Y. and J. Shan, 2014. A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences, ISPRS Journal of Photogrammetry and Remote Sensing, 90: 83-95.   DOI