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Proceedings Paper

SAR image registration based on SIFT and MSA
Author(s): Zhaoxiang Yi; Xiongmei Zhang; Xiaodong Mu; Kui Wang; Jianshe Song
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Paper 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.

Paper Details

Date Published: 21 February 2014
PDF: 8 pages
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
Show Author Affiliations
Zhaoxiang Yi, Xi'an Research Institute of High-Tech (China)
Xiongmei Zhang, Xi'an Research Institute of High-Tech (China)
Xiaodong Mu, Xi'an Research Institute of High-Tech (China)
Kui Wang, Xi'an Research Institute of High-Tech (China)
Jianshe Song, Xi'an Research Institute of High-Tech (China)


Published in SPIE Proceedings Vol. 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
Jorge Ojeda-Castaneda; Shensheng Han; Ping Jia; Jiancheng Fang; Dianyuan Fan; Liejia Qian; Yuqiu Gu; Xueqing Yan, Editor(s)

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