Using vector building maps to aid in generating seams for low-attitude aerial orthoimage mosaicking: Advantages in avoiding the crossing of buildings

Dongliang Wang, Wei Cao, Xiaoping Xin, Quanqin Shao, Matthew Brolly, Jianhua Xiao, Youchuan Wan, Yongjun Zhang

Research output: Contribution to journalArticleResearchpeer-review

Abstract

A novel seam detection approach based on vector building maps is presented for low-attitude aerial orthoimage mosaicking. The approach tracks the centerlines between vector buildings to generate the candidate seams that avoid crossing buildings existing in maps. The candidate seams are then refined by considering their surrounding pixels to minimize the visual transition between the images to be mosaicked. After the refinement of the candidate seams, the final seams further bypass most of the buildings that are not updated into vector maps. Finally, three groups of aerial imagery from different urban densities are employed to test the proposed approach. The experimental results illustrate the advantages of the proposed approach in avoiding the crossing of buildings. The computational efficiency of the proposed approach is also significantly higher than that of Dijkstra’s algorithm.
Original languageEnglish
Pages (from-to)207-224
Number of pages18
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume125
DOIs
Publication statusPublished - 11 Feb 2017

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Antennas
Computational efficiency
Pixels

Keywords

  • Aerial image mosaicking
  • Vector building map
  • Seam detection

Cite this

Wang, Dongliang ; Cao, Wei ; Xin, Xiaoping ; Shao, Quanqin ; Brolly, Matthew ; Xiao, Jianhua ; Wan, Youchuan ; Zhang, Yongjun. / Using vector building maps to aid in generating seams for low-attitude aerial orthoimage mosaicking: Advantages in avoiding the crossing of buildings. In: ISPRS Journal of Photogrammetry and Remote Sensing. 2017 ; Vol. 125. pp. 207-224.
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abstract = "A novel seam detection approach based on vector building maps is presented for low-attitude aerial orthoimage mosaicking. The approach tracks the centerlines between vector buildings to generate the candidate seams that avoid crossing buildings existing in maps. The candidate seams are then refined by considering their surrounding pixels to minimize the visual transition between the images to be mosaicked. After the refinement of the candidate seams, the final seams further bypass most of the buildings that are not updated into vector maps. Finally, three groups of aerial imagery from different urban densities are employed to test the proposed approach. The experimental results illustrate the advantages of the proposed approach in avoiding the crossing of buildings. The computational efficiency of the proposed approach is also significantly higher than that of Dijkstra’s algorithm.",
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Using vector building maps to aid in generating seams for low-attitude aerial orthoimage mosaicking: Advantages in avoiding the crossing of buildings. / Wang, Dongliang; Cao, Wei; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Xiao, Jianhua; Wan, Youchuan; Zhang, Yongjun.

In: ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 125, 11.02.2017, p. 207-224.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Wang, Dongliang

AU - Cao, Wei

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AU - Shao, Quanqin

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AB - A novel seam detection approach based on vector building maps is presented for low-attitude aerial orthoimage mosaicking. The approach tracks the centerlines between vector buildings to generate the candidate seams that avoid crossing buildings existing in maps. The candidate seams are then refined by considering their surrounding pixels to minimize the visual transition between the images to be mosaicked. After the refinement of the candidate seams, the final seams further bypass most of the buildings that are not updated into vector maps. Finally, three groups of aerial imagery from different urban densities are employed to test the proposed approach. The experimental results illustrate the advantages of the proposed approach in avoiding the crossing of buildings. The computational efficiency of the proposed approach is also significantly higher than that of Dijkstra’s algorithm.

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