A Robust Photogrammetric Processing Method of Low-Altitude UAV Images

Remote Sensing

Mingyao Ai¹  Qingwu Hu¹  Jiayuan Li¹  Ming Wang¹  Hui Yuan¹  Shaohua Wang³  Gonzalo Pajares Martinsanz² 

[1] School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China; E-Mails:School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;;International School of Software, Wuhan University, Wuhan 430079, China; E-Mail:

关键词: strip auto-arrangement;    BAoSIFT;    dense match;    digital orthophoto maps (DOM);    unmanned aerial vehicles (UAV);   

DOI  :  10.3390/rs70302302

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.