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Remote Sens. 2015, 7(3), 2302-2333; doi:10.3390/rs70302302

A Robust Photogrammetric Processing Method of Low-Altitude UAV Images

1
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2
State Key Laboratory of Information Engineering, Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
3
International School of Software, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares Martinsanz and Prasad S. Thenkabail
Received: 21 July 2014 / Revised: 8 February 2015 / Accepted: 15 February 2015 / Published: 26 February 2015

Abstract

Low-altitude Unmanned Aerial Vehicles (UAV) images which include distortion, illumination variance, and large rotation angles are facing multiple challenges of image orientation and image processing. In this paper, a robust and convenient photogrammetric approach is proposed for processing low-altitude UAV images, involving a strip management method to automatically build a standardized regional aerial triangle (AT) network, a parallel inner orientation algorithm, a ground control points (GCPs) predicting method, and an improved Scale Invariant Feature Transform (SIFT) method to produce large number of evenly distributed reliable tie points for bundle adjustment (BA). A multi-view matching approach is improved to produce Digital Surface Models (DSM) and Digital Orthophoto Maps (DOM) for 3D visualization. Experimental results show that the proposed approach is robust and feasible for photogrammetric processing of low-altitude UAV images and 3D visualization of products. View Full-Text
Keywords: strip auto-arrangement; BAoSIFT; dense match; digital orthophoto maps (DOM); unmanned aerial vehicles (UAV) strip auto-arrangement; BAoSIFT; dense match; digital orthophoto maps (DOM); unmanned aerial vehicles (UAV)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ai, M.; Hu, Q.; Li, J.; Wang, M.; Yuan, H.; Wang, S. A Robust Photogrammetric Processing Method of Low-Altitude UAV Images. Remote Sens. 2015, 7, 2302-2333.

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