A graph-based approach for the co-registration refinement of very-high-resolution imagery and digital line graphic data

ABSTRACT

Co-registration refinement of very-high-resolution (VHR) imagery and digital-line-graphic (DLG) data is an important procedure before data fusion and analysis. However, existing approaches either make little consideration of topological relations between features or have to extract complete objects, which is very challenging. In this study, to overcome the drawbacks mentioned above, a graph-based approach is presented for the co-registering of VHR imagery and DLG data. Our proposed method uses a graph to represent the topological relations between buildings in both data sources, which helps match buildings in the two data sources and compute the affine transformation parameters. The proposed method is validated on three diverse VHR images, and two objective evaluation metrics (correctness and quality rate) are computed to evaluate its performance. It is shown that correctness and quality rate are averagely improved by 37.3% and 46.7%, respectively, after co-registration. These results indicate that our proposed method is effective in the co-registration of VHR imagery and DLG data.

Acknowledgement

The authors would like to thank Aaron R. Gall and Xiyan Hao for improving the language.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [41471315].