2 January 2018 Point-matching algorithm based on local neighborhood information for remote sensing image registration
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Abstract
Robust feature point matching is a critical procedure in feature-based remote sensing image registration. A point-matching algorithm is proposed, which uses the similarity of local neighborhood information of point features. First, we establish a set of initial correspondences. Then we focus on removing incorrect correspondences (outliers) by local neighborhood information and increasing the number of correct correspondences (inliers). Finally, a global structure constraint is constructed for each remaining correct correspondence to increase the number of inliers and raise the correct rate simultaneously. Experimental results compared with three state-of-the-art methods illustrate that the proposed method can find more correct matching points with high accuracy.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Yue Wu, Yue Wu, Wenping Ma, Wenping Ma, Jun Zhang, Jun Zhang, Yong Zhong, Yong Zhong, Liang Liu, Liang Liu, } "Point-matching algorithm based on local neighborhood information for remote sensing image registration," Journal of Applied Remote Sensing 12(1), 016002 (2 January 2018). https://doi.org/10.1117/1.JRS.12.016002 . Submission: Received: 28 July 2017; Accepted: 15 November 2017
Received: 28 July 2017; Accepted: 15 November 2017; Published: 2 January 2018
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