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Appl. Sci. 2017, 7(10), 965; doi:10.3390/app7100965

Registration of Urban Aerial Image and LiDAR Based on Line Vectors

1
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2
Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing, Tianjin 300301, China
*
Author to whom correspondence should be addressed.
Received: 30 July 2017 / Revised: 14 September 2017 / Accepted: 19 September 2017 / Published: 21 September 2017
(This article belongs to the Section Computer Science and Electrical Engineering)
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Abstract

In a traditional registration of a single aerial image with airborne light detection and ranging (LiDAR) data using linear features that regard line direction as a control or linear features as constraints in the solution, lacking the constraint of linear position leads to the error propagation of the adjustment model. To solve this problem, this paper presents a line vector-based registration mode (LVR) in which image rays and LiDAR lines are expressed by a line vector that integrates the line direction and the line position. A registration equation of line vector is set up by coplanar imaging rays and corresponding control lines. Three types of datasets consisting of synthetic, theInternational Society for Photogrammetry and Remote Sensing (ISPRS) test project, and real aerial data are used. A group of progressive experiments is undertaken to evaluate the robustness of the LVR. Experimental results demonstrate that the integrated line direction and the line position contributes a great deal to the theoretical and real accuracies of the unknowns, as well as the stability of the adjustment model. This paper provides a new suggestion that, for a single image and LiDAR data, registration in urban areas can be accomplished by accommodating rich line features. View Full-Text
Keywords: image registration; laser radar; multisensor data; urban areas; aerial image; linear feature image registration; laser radar; multisensor data; urban areas; aerial image; linear feature
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MDPI and ACS Style

Sheng, Q.; Wang, Q.; Zhang, X.; Wang, B.; Zhang, B.; Zhang, Z. Registration of Urban Aerial Image and LiDAR Based on Line Vectors. Appl. Sci. 2017, 7, 965.

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