Automatic image registration by local descriptors in remote sensing

Xiao-Jun Liu; Jie Yang; Hong-Bin Shen

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Automatic image registration by local descriptors in remote sensing

机译：Automatic image registration by local descriptors in remote sensing

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摘要

Registration of multiresolution and multisensor images is a challenging problem in the research area of remote sensing. Conventional image registration algorithms have greatly suffered from control points selected manually. In this study, we propose a novel method for automatic affine image registration based on local descriptors, called automatic image registration by local descriptors (AIRLD). In this algorithm, we first apply the Harris-affine method to extract the interesting points of the given images, and then they are used to calculate the affine invariant feature descriptors. These descriptors are combined through the normalized mutual information (NMI) method to obtain robust matching control points in both reference and sensed images automatically. Finally, we show that subpixel registration accuracy can be reached by means of a least-square fitting of a paraboloid function to the surface generated by the NMIs of the control point neighbors. Experimental results show that our method can provide better accuracy than the conventional registration process.

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来源
《Optical Engineering》 |2008年第8期|087206-1-087206-9-0|共9页
作者
Xiao-Jun Liu; Jie Yang; Hong-Bin Shen;
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作者单位

Shanghai Jiaotong University, Institute of Image Processing and Pattern Recognition, 800 Dongchuan Road, Shanghai 200240, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类光学仪器;
关键词
image registration; local descriptors; Harris affine; normalized mutual information; remote sensing;

Automatic image registration by local descriptors in remote sensing

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