11 April 2018 Unmanned aerial vehicle oblique image registration using an ASIFT-based matching method
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Abstract
Low-altitude unmanned aerial vehicles (UAV) are widely used to acquire aerial photographs, some of which are oblique and have a large angle of view. Precise, automatic registration of such images is a challenge for conventional image processing methods. We present an affine scale-invariant feature transform (ASIFT)-based method that can register UAV oblique images at a subpixel level. First, we used the ASIFT algorithm to collect initial feature points. Positions of the feature points on corresponding local images were then corrected using the weighted least square matching (WLSM) method. Mismatching points were discarded and a local transform model was estimated using the adaptive normalized cross correlation algorithm, which also provides initial parameters for WLSM. Experiments show that sufficient feature points are collected to successfully register, to the subpixel level, UAV and other images with large angle-of-view variations and strong affine distortions. The proposed method improves the matching accuracy of previous UAV image registration methods.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Chengyi Wang, Jingbo Chen, Jiansheng Chen, Anzhi Yue, Dongxu He, Qingqing Huang, Yi Zhang, "Unmanned aerial vehicle oblique image registration using an ASIFT-based matching method," Journal of Applied Remote Sensing 12(2), 025002 (11 April 2018). https://doi.org/10.1117/1.JRS.12.025002 Submission: Received 20 August 2017; Accepted 21 March 2018
Submission: Received 20 August 2017; Accepted 21 March 2018
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