Remote Sensing Image Registration Based on Phase Congruency Feature Detection and Spatial Constraint Matching

In this paper, a novel remote sensing image registration method based on phase congruency (PC) and spatial constraint is proposed. PC can provide intrinsic and meaningful image features, even when there are complex intensity changes or noise. Image features will be well detected from the corresponding PC images by the SAR-SIFT operator. It means that the feature detection methods in the frequency domain (PC) and the spatial domain (SAR-SIFT operator) are combined. To further improve the result of registration, spatial constraints, including point and line constraint, are established by utilizing the position and orientation information. Then, one to more matches can be removed and the influence of adjacent point can be greatly eliminated. The experimental results demonstrate that our method can obtain a better registration performance with higher accuracy and more correct correspondences than the state-of-the-art methods, such as SIFT, SAR-SIFT, SURF, PSO-SIFT, RIFT, and GLPM.

• Publication year

  2018

• Venue

  IEEE Access

• Publication date

  2018-12-10

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/ACCESS.2018.2883410
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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