Paper
8 December 2015 Automatic and robust method for registration of optical imagery with point cloud data
Author Affiliations +
Proceedings Volume 9875, Eighth International Conference on Machine Vision (ICMV 2015); 98751B (2015) https://doi.org/10.1117/12.2228798
Event: Eighth International Conference on Machine Vision, 2015, Barcelona, Spain
Abstract
Aim to the difficulty of automatic and robust registration of optical imagery with point cloud data, this paper propose a new method based on SIFT and Mutual Information (MI). The SIFT features are firstly extracted and matched, whose result is used to derive the coarse geometric relationship between the optical imagery and the point cloud data. Secondly, the MI-based similarity measure is used to derive the conjugate points. And then the RANSAC algorithm is adopted to eliminate the erroneous matching points. Repeating the procedure of MI matching and mismatching points deletion until the finest pyramid image level. Using the matching results, the transform model is determined. The experiments have been made and they demonstrate the potential of the MI-based measure for the registration of optical imagery with the point cloud data, and this highlight the feasibility and robustness of the method proposed in this paper to automated registration of multi-modal, multi-temporal remote sensing data for a wide range of applications.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yingdan Wu and Yang Ming "Automatic and robust method for registration of optical imagery with point cloud data", Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98751B (8 December 2015); https://doi.org/10.1117/12.2228798
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KEYWORDS
Image registration

Clouds

Feature extraction

Affine motion model

Data modeling

LIDAR

Medical imaging

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