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XIANG Yuming, TENG Fei, WANG Linhui, et al. Orthorectification of high-resolution SAR images in island regions based on fast multimodal registration[J]. Journal of Radars, in press. doi: 10.12000/JR24022
Citation: XIANG Yuming, TENG Fei, WANG Linhui, et al. Orthorectification of high-resolution SAR images in island regions based on fast multimodal registration[J]. Journal of Radars, in press. doi: 10.12000/JR24022
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Orthorectification of High-resolution SAR Images in Island Regions Based on Fast Multimodal Registration

doi: 10.12000/JR24022
  • 1.

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • 2.

    Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China

  • 3.

    School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Funds:  Key Research Program of Frontier Sciences, Chinese Academy of Sciences (ZDBS-LY-JSC036), The National Natural Science Foundation of China (61901439)
More Information
  • Corresponding author: XIANG Yuming, xiangym@aircas.ac.cn
  • Received Date: 2024-02-03
  • Rev Recd Date: 2024-03-27
    • Available Online: 2024-04-02
    Abstract
  • With the successive launch of high-resolution Synthetic Aperture Radar (SAR) satellites, conducting all-weather, all-time high-precision observation of island regions with variable weather conditions has become feasible. As a key preprocessing step in various remote sensing applications, orthorectification relies on high-precision control points to correct the geometric positioning errors of SAR images. However, obtaining artificial control points that meet SAR correction requirements in island areas is costly and risky. To address this challenge, this study first proposes a rapid registration algorithm for optical and SAR heterogeneous images, and then automatically extracts control points based on an optical reference base map, achieving orthorectification of SAR images in island regions. The proposed registration algorithm consists of two stages: constructing dense common features of heterogeneous images; performing pixel-by-pixel matching on the down-sampled features, to avoid the issue of low repeatability of feature points in heterogeneous images. To reduce the matching complexity, a land sea segmentation mask is introduced to limit the search range. Subsequently, local fine matching is applied to the preliminary matched points to reduce inaccuracies introduced by down-sampling. Meanwhile, uniformly sampled coastline points are introduced to enhance the uniformity of the matching results, and orthorectified images are generated through a piecewise linear transformation model, ensuring the overall correction accuracy in sparse island areas. This algorithm performs excellently on the high-resolution SAR images of multiple scenes in island regions, with an average positioning error of 3.2 m and a complete scene correction time of only 17.3 s, both these values are superior to various existing advanced heterogeneous registration and correction algorithms, demonstrating the great potential of the proposed algorithm in engineering applications.

     

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