Registration of Optical and SAR Satellite Images by Exploring the Spatial Relationship of the Improved SIFT

@article{Fan2013RegistrationOO,
  title={Registration of Optical and SAR Satellite Images by Exploring the Spatial Relationship of the Improved SIFT},
  author={Bin Fan and Chunlei Huo and Chunhong Pan and Qingqun Kong},
  journal={IEEE Geoscience and Remote Sensing Letters},
  year={2013},
  volume={10},
  pages={657-661}
}
  • Bin Fan, Chunlei Huo, +1 author Qingqun Kong
  • Published in
    IEEE Geoscience and Remote…
    2013
  • Mathematics, Computer Science
  • Although feature-based methods have been successfully developed in the past decades for the registration of optical images, the registration of optical and synthetic aperture radar (SAR) images is still a challenging problem in remote sensing. In this letter, an improved version of the scale-invariant feature transform is first proposed to obtain initial matching features from optical and SAR images. Then, the initial matching features are refined by exploring their spatial relationship. The… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Figures, Tables, and Topics from this paper.

    Explore Further: Topics Discussed in This Paper

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 79 CITATIONS

    Multimodal Remote Sensing Image Registration With Accuracy Estimation at Local and Global Scales

    VIEW 11 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    Automatic Optical-to-SAR Image Registration by Iterative Line Extraction and Voronoi Integrated Spectral Point Matching

    VIEW 16 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    GGSOR: A Gaussian-Gamma-Shaped bi-windows based descriptor for optical and SAR images matching

    • Min Chen, Qing Zhu, Jun Zhu
    • Computer Science
    • 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
    • 2015
    VIEW 5 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    A New Structure-Based Coregistration Method for Near-Field Ground-Based MIMO Tomographic SAR

    • Gen Li, Yunzhi Zhu, +4 authors Min-Kun Liu
    • Computer Science
    • IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
    • 2019
    VIEW 1 EXCERPT
    CITES METHODS

    Automatic Registration of Optical and SAR Images VIA Improved Phase Congruency

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Fast Color Blending for Seamless Image Stitching

    VIEW 1 EXCERPT
    CITES BACKGROUND

    FILTER CITATIONS BY YEAR

    2013
    2020

    CITATION STATISTICS

    • 6 Highly Influenced Citations

    • Averaged 13 Citations per year from 2017 through 2019

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 16 REFERENCES

    A Performance Evaluation of Local Descriptors

    VIEW 11 EXCERPTS
    HIGHLY INFLUENTIAL

    BFSIFT: A Novel Method to Find Feature Matches for SAR Image Registration

    VIEW 3 EXCERPTS

    Automatic Image Registration Through Image Segmentation and SIFT

    VIEW 1 EXCERPT

    Towards reliable matching of images containing repetitive patterns

    VIEW 1 EXCERPT

    Mutual-Information-Based Registration of TerraSAR-X and Ikonos Imagery in Urban Areas

    VIEW 1 EXCERPT