23 April 2012 Automated two-dimensional-three-dimensional registration using intensity gradients for three-dimensional reconstruction
Author Affiliations +
J. of Applied Remote Sensing, 6(1), 063517 (2012). doi:10.1117/1.JRS.6.063517
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.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Prakash Duraisamy, Yassine Belkhouche, Bill P. Buckles, Stephen Jackson, Kamesh Namuduri, "Automated two-dimensional-three-dimensional registration using intensity gradients for three-dimensional reconstruction," Journal of Applied Remote Sensing 6(1), 063517 (23 April 2012). https://doi.org/10.1117/1.JRS.6.063517

3D modeling



3D image processing

Image registration

Data modeling

Visual process modeling

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