Modified RANSAC for SIFT-Based InSAR Image Registration

نویسندگان

  • Yang Wang
  • Haifeng Huang
  • Zhen Dong
  • Manqing Wu
چکیده

Abstract—In this paper, we propose a modified version of the Random Sample Consensus (RANSAC) method for Interferometric Synthetic Aperture Radar (InSAR) image registration based on the ScaleInvariant Feature Transform (SIFT). Because of speckle, the “maximization of inliers” criterion in the original RANSAC cannot obtain the optimal results. Since in InSAR image registration, the registration accuracy is in inverse proportion to number of residues. Therefore, we modify the old criterion with a new one — Minimization of residues — to obtain the optimal results. We tested our method on a variety of real data from different sensors, and the experimental results demonstrated the validity and robustness of the proposed method.

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تاریخ انتشار 2014