Research Papers

Automated two-dimensional–three-dimensional registration using intensity gradients for three-dimensional reconstruction

[+] Author Affiliations
Prakash Duraisamy, Yassine Belkhouche, Bill Buckles

University of North Texas, Department of Computer Science and Engineering, Denton, Texas 76203

Stephen Jackson

University of North Texas, Department of Mathematics, Denton, Texas 76203

Kamesh Namuduri

University of North Texas, Department of Electrical Engineering, Denton, Texas 76203

J. Appl. Remote Sens. 6(1), 063517 (Apr 23, 2012). doi:10.1117/1.JRS.6.063517
History: Received October 31, 2011; Revised January 26, 2012; Accepted February 1, 2012
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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.

Figures in this Article
© 2012 Society of Photo-Optical Instrumentation Engineers

Topics

Cameras ; LIDAR

Citation

Prakash Duraisamy ; Yassine Belkhouche ; Stephen Jackson ; Kamesh Namuduri and Bill Buckles
"Automated two-dimensional–three-dimensional registration using intensity gradients for three-dimensional reconstruction", J. Appl. Remote Sens. 6(1), 063517 (Apr 23, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063517


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