Superpixel-based optimal seamline detection in the gradient domain via graph cuts for orthoimage mosaicking

ABSTRACT

This paper presents an optimal seamline detection method for orthoimage mosaicking. To ensure that the detected optimal seamlines avoid crossing many obvious objects, we first design a simple but effective criterion in the gradient domain in lieu of the traditionally used intensity domain to measure the visibility of the seam. Thereafter, we fuse this new criterion into the graph cuts energy minimisation framework to globally find the last optimal seamlines. Instead of finding the optimal solutions of seamlines in overlap regions via graph cuts among the entire set of pixels, we first find them among superpixels created from input images and then refine them in the pixel level, which greatly improves the efficiency of the global graph cuts energy optimisation because the number of elements in graph cuts dramatically decreases. Experimental results on orthoimages show that our proposed method is capable of finding high-quality seamlines for orthoimage mosaicking, and outperforms state-of-the-art algorithms and software.

Acknowledgments

The authors want to thank two anonymous reviewers for their valuable comments and suggestions to improve the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was partially supported by the National Natural Science Foundation of China (Project No. 41571436); the National Key Research and Development Program of China (Project No. 2017YFB1302400); the Hubei Province Science and Technology Support Program, China (Project No. 2015BAA027); the National Natural Science Foundation of China under Grant 91438203; and LIESMARS Special Research Funding.