The Impact of Different Seamline Production Methods on the Production of Orthophoto Mosaic in Urban Area

Year 2017, Volume: 17 Issue: 2, 620 - 627, 31.08.2017

Hakan, Karabörk , Mehmet Ozan Fakıoğlu

Abstract

Evolving software and image acquisition systems have reduced orthophoto production time, positively impacted product quality and reduced production costs. Quality of the orthophoto production process is influenced by the exterior orientation parameters and the digital elevation model. The seamline used in the mosaicking is also affected by the mathematical methods used.It is certain that determining the most accurate mathematical method to be used in seamline production will reduce time in orthophoto production and increase product quality.

In the test area (urban area) determined in this study,mosaic production withobject-based recognition, adaptive feathering, smart seams method and the closest-to-camera-center methods have been realized using images with a ground sampling distance (GSD) of 30 cm and 10 cm. As a result, the most successful results have been obtained using object-based recognition method.

Keywords

Photogrammetry, Orthophoto, Seamline, Ortho Mosaic

References

• Chen, Q., Sun, M., Hu, X., Zhang, Z., 2014, Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model, Remote Sens. 2014, 6, 12334-12359.
• Chon, J., H, Kim., C, Lin., 2010, Seam-Line Determination for Image Mosaicking: A Technique Minimizing the Maximum Local Mismatch and the Global Cost, ISPRS Journal of Photogrammetry and Remote Sensing, 65 (1), 86–92.
• Milgram, D.L., 1975, Computer methods for creating photomosaics, IEEE Trans. Comput., 24, 1113–1119. Pan, J., Wang, M., 2011, A seam-line optimized method based on difference image and gradient image, IEEE., 978-1-61284, 848-8/11.
• Pan, J., Wang, M., Li, J., Yuan, S., Hu, F., 2015, Region change rate-driven seamline determination method, ISPRS Journal of Photogrammetry and Remote Sensing, 105,141–154.
• Pan, J., Yuan, S., Li, J., Wu, B., 2017, Seamline optimization based on ground objects classes for orthoimage mosaicking, Remote Sensing Letters, 8:3, 280-289.
• Saito,S., Arai, R.,Aoki,Y., 2015, Seamline Determination Based on Semantic Segmentation for Aerial Image Mosaicking, IEEE. Translations and content mining are permitted for academic research only, 3, 2847- 2856.
• Zhu, S.L., Yang, X.H., 2000, The seamline removing in the generation of orthophoto maps, International Archives of Photogrammetry and Remote Sensing.,Vol. XXXIIIPart B4, 1247-1251.
• Wan, Y., Wang, D., Xiao, J., Lai, X., Xu, J., 2012, Automatic determination of seamlines for aerial image mosaicking based on vector roads alone, ISPRS Journal of Photogrammetry and Remote Sensing, 76, 1–10.
• 1-https://hexagongeospatial.fluidtopics.net/book, (10.07.2016)
• 2-http://www.trimble.com/imaging/inpho.aspx, (20.07.2016)