Point-matching algorithm based on local neighborhood information for remote sensing image registration

Yue Wu; Wenping Ma; Jun Zhang; Yong Zhong; Liang Liu

doi:10.1117/1.JRS.12.016002

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2 January 2018 Point-matching algorithm based on local neighborhood information for remote sensing image registration

Yue Wu, Wenping Ma, Jun Zhang, Yong Zhong, Liang Liu

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J. of Applied Remote Sensing, 12(1), 016002 (2018). https://doi.org/10.1117/1.JRS.12.016002

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.

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Yue Wu, Wenping Ma, Jun Zhang, Yong Zhong, and 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

Received: 28 July 2017; Accepted: 15 November 2017; Published: 2 January 2018

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