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Journal of Applied Remote Sensing

Automated two-dimensional-three-dimensional registration using intensity gradients for three-dimensional reconstruction
Author(s): Prakash Duraisamy; Yassine Belkhouche; Bill P. Buckles; Stephen Jackson; Kamesh Namuduri
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Paper Abstract

We develop a robust framework for the registration of light detection and ranging (LiDAR) images with 2-D visual images using a method based on intensity gradients. Our proposed algorithm consists of two steps. In the first step, we extract lines from the digital surface model (DSM) given by the LiDAR image, then we use intensity gradients to register the extracted lines from the LiDAR image onto the visual image to roughly estimate the extrinsic parameters of the calibrated camera. In our approach, we overcome some of the limitations of 3-D reconstruction methods based on the matching of features between the two images. Our algorithm achieves an accuracy for the camera pose recovery of about 98% for the synthetic images tested, and an accuracy of about 95% for the real-world images we tested, which were from the downtown New Orleans area.

Paper Details

Date Published: 23 April 2012
PDF: 14 pages
J. Appl. Rem. Sens. 6(1) 063517 doi: 10.1117/1.JRS.6.063517
Published in: Journal of Applied Remote Sensing Volume 6, Issue 1
Show Author Affiliations
Prakash Duraisamy, Univ. of North Texas (United States)
Yassine Belkhouche, Univ. of North Texas (United States)
Bill P. Buckles, Univ. of North Texas (United States)
Stephen Jackson, Univ. of North Texas (United States)
Kamesh Namuduri, Univ. of North Texas (United States)

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