Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/89312
Title: | A phase-congruency-based scene abstraction approach for 2D-3D registration of aerial optical and LiDAR images | Authors: | Megahed, Y Shaker, A Yan, WY |
Issue Date: | 2020 | Source: | IEEE journal of selected topics in applied earth observations and remote sensing, 2020, v. 14, p. 964-981 | Abstract: | Registration of aerial images to enrich 3-D light detection and ranging (LiDAR) points with radiometric information can enhance the capability of object detection, scene classification, and semantic segmentation. However, airborne LiDAR data may not always come with on-board optical images collected during the same flight mission. Indirect georeferencing can be adopted, if ancillary imagery data are found available. Nevertheless, automatic recognition of control primitives in LiDAR and imagery datasets becomes challenging, especially when they are collected on different dates. This article proposes a generic registration mechanism based on using the phase congruency (PC) model and scene abstraction to overcome the stated challenges. The approach relies on the use of a PC measure to compute the image moments that determine the study scene's edges. Potential candidate points can be identified based on thresholding the image moments' values. A shape context descriptor is adopted to automatically pair symmetric candidate points to produce a final set of control points. Coordinate transformation parameters between the two datasets were estimated using a least squares adjustment for four registration models: first- (affine), second-, third-order polynomials, and direct linear transform models. Datasets covering different urban landscapes were used to examine the proposed workflow. The root-mean-square error of the registration is between one and two pixels. The proposed workflow is found to be computationally efficient especially with small-sized datasets, and generic enough to be applied in registering various imagery data and LiDAR point clouds. | Keywords: | Aerial imagery Airborne light detection and ranging (LiDAR) Canny edge detector Image registration Phase congruency (PC) Scene abstraction Shape context |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE journal of selected topics in applied earth observations and remote sensing | ISSN: | 1939-1404 | EISSN: | 2151-1535 | DOI: | 10.1109/JSTARS.2020.3033770 | Rights: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ The following publication Y. Megahed, A. Shaker and W. Y. Yan, "A Phase-Congruency-Based Scene Abstraction Approach for 2D-3D Registration of Aerial Optical and LiDAR Images," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 964-981, 2021 is available at https://dx.doi.org/10.1109/JSTARS.2020.3033770. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
09239903.pdf | 11.48 MB | Adobe PDF | View/Open |
Page views
32
Last Week
0
0
Last month
Citations as of May 28, 2023
Downloads
24
Citations as of May 28, 2023
SCOPUSTM
Citations
5
Citations as of Jun 2, 2023
WEB OF SCIENCETM
Citations
5
Citations as of Jun 1, 2023

Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.