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

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...

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Bibliographic Details
Published inInternational journal of remote sensing Vol. 39; no. 12; pp. 3908 - 3925
Main Authors Li, Li, Yao, Jian, Shi, Shuzhu, Yuan, Shenggu, Zhang, Yaxuan, Li, Jie
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 18.06.2018
Taylor & Francis Ltd
Subjects
Algorithms
Criteria
Detection
Energy conservation
Frameworks
Methods
Object recognition
Optimization
Pixels
Solutions
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Summary: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.
ISSN:0143-1161
1366-5901
DOI:10.1080/01431161.2018.1447164