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Proceedings Paper

A method of fast mosaic for massive UAV images
Author(s): Ren Xiang; Min Sun; Cheng Jiang; Lei Liu; Hui Zheng; Xiaodong Li
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Paper Abstract

With the development of UAV technology, UAVs are used widely in multiple fields such as agriculture, forest protection, mineral exploration, natural disaster management and surveillances of public security events. In contrast of traditional manned aerial remote sensing platforms, UAVs are cheaper and more flexible to use. So users can obtain massive image data with UAVs, but this requires a lot of time to process the image data, for example, Pix4UAV need approximately 10 hours to process 1000 images in a high performance PC. But disaster management and many other fields require quick respond which is hard to realize with massive image data. Aiming at improving the disadvantage of high time consumption and manual interaction, in this article a solution of fast UAV image stitching is raised. GPS and POS data are used to pre-process the original images from UAV, belts and relation between belts and images are recognized automatically by the program, in the same time useless images are picked out. This can boost the progress of finding match points between images. Levenberg-Marquard algorithm is improved so that parallel computing can be applied to shorten the time of global optimization notably. Besides traditional mosaic result, it can also generate superoverlay result for Google Earth, which can provide a fast and easy way to show the result data. In order to verify the feasibility of this method, a fast mosaic system of massive UAV images is developed, which is fully automated and no manual interaction is needed after original images and GPS data are provided. A test using 800 images of Kelan River in Xinjiang Province shows that this system can reduce 35%-50% time consumption in contrast of traditional methods, and increases respond speed of UAV image processing rapidly.

Paper Details

Date Published: 8 November 2014
PDF: 9 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 92603W (8 November 2014); doi: 10.1117/12.2069201
Show Author Affiliations
Ren Xiang, Peking Univ. (China)
Min Sun, Peking Univ. (China)
Cheng Jiang, Peking Univ. (China)
Lei Liu, Peking Univ. (China)
Hui Zheng, China Univ. of Mining and Technology (China)
Xiaodong Li, Peking Univ. (China)


Published in SPIE Proceedings Vol. 9260:
Land Surface Remote Sensing II
Thomas J. Jackson; Jing Ming Chen; Peng Gong; Shunlin Liang, Editor(s)

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