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Open AccessArticle

Optimal Seamline Detection for Orthoimage Mosaicking Based on DSM and Improved JPS Algorithm

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College of Marine Science and Technology, China University of Geosciences, Wuhan 430074, Hubei, China
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Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, Hubei, China
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Faculty of Computer sciences, China University of Geosciences, Wuhan 430074, Hubei, China
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Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 821; https://doi.org/10.3390/rs10060821
Received: 10 April 2018 / Revised: 5 May 2018 / Accepted: 17 May 2018 / Published: 25 May 2018
Based on the digital surface model (DSM) and jump point search (JPS) algorithm, this study proposed a novel approach to detect the optimal seamline for orthoimage mosaicking. By threshold segmentation, DSM was first identified as ground regions and obstacle regions (e.g., buildings, trees, and cars). Then, the mathematical morphology method was used to make the edge of obstacles more prominent. Subsequently, the processed DSM was considered as a uniform-cost grid map, and the JPS algorithm was improved and employed to search for key jump points in the map. Meanwhile, the jump points would be evaluated according to an optimized function, finally generating a minimum cost path as the optimal seamline. Furthermore, the search strategy was modified to avoid search failure when the search map was completely blocked by obstacles in the search direction. Comparison of the proposed method and the Dijkstra’s algorithm was carried out based on two groups of image data with different characteristics. Results showed the following: (1) the proposed method could detect better seamlines near the centerlines of the overlap regions, crossing far fewer ground objects; (2) the efficiency and resource consumption were greatly improved since the improved JPS algorithm skips many image pixels without them being explicitly evaluated. In general, based on DSM, the proposed method combining threshold segmentation, mathematical morphology, and improved JPS algorithms was helpful for detecting the optimal seamline for orthoimage mosaicking. View Full-Text
Keywords: orthoimage mosaicking; seamline; digital surface model; jump point search algorithm orthoimage mosaicking; seamline; digital surface model; jump point search algorithm
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Chen, G.; Chen, S.; Li, X.; Zhou, P.; Zhou, Z. Optimal Seamline Detection for Orthoimage Mosaicking Based on DSM and Improved JPS Algorithm. Remote Sens. 2018, 10, 821.

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