21 February 2014 SAR image registration based on SIFT and MSA
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Abstract
Referring to the problem of SAR image registration, an image registration method based on Scale Invariant Feature Transform (SIFT) and Multi-Scale Autoconvolution (MSA) is proposed. Based on the extraction of SIFT descriptors and the MSA affine invariant moments of the region around the keypoints, the feature fusion method based on canonical correlation analysis (CCA) is employed to fuse them together to be a new descriptor. After the control points are rough matched, the distance and gray correlation around the rough matched points are combined to build the similarity matrix and the singular value decomposition (SVD) method is employed to realize precise image registration. Finally, the affine transformation parameters are obtained and the images are registered. Experimental results show that the proposed method outperforms the SIFT method and achieves high accuracy in sub-pixel level.
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Zhaoxiang Yi, Zhaoxiang Yi, Xiongmei Zhang, Xiongmei Zhang, Xiaodong Mu, Xiaodong Mu, Kui Wang, Kui Wang, Jianshe Song, Jianshe Song, } "SAR image registration based on SIFT and MSA", Proc. SPIE 9142, Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics: Optical Imaging, Remote Sensing, and Laser-Matter Interaction 2013, 91421K (21 February 2014); doi: 10.1117/12.2054155; https://doi.org/10.1117/12.2054155
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