THE DIRECT REGISTRATION OF LIDAR POINT CLOUDS AND HIGH RESOLUTION 
IMAGE BASED ON LINEAR FEATURE BY INTRODUCING AN UNKN OWN 
PARAMETER 
Yao. Chunjing.* * , Gao. Guang.? 
“ Dept. of Remote Sensing and Information Engineering, Wuhan University , Luoyu Road 129, Wuhan City, P. R. 
China 
yaocj@whu.edu.cn 
Commission IV, WG IV/2, IV/4: Point Cloud Processing, Management & Visualization 
KEY WORDS: Airborne LIDAR, Linear Feature, Registration, Scale Analysis 
ABSTRACT: 
The registration between optical images and point clouds is the first task when the combination of these two datasets is concerned. 
Due to the discrete nature of the point clouds, and the 2D-3D transformation in particular, a tie points based registration strategy 
which is commonly adopted in image-to-image registration is hard to be used directly in this scenario. A derived collinear equation 
describing the map relationship between an image point and a ground point is used as the mathematical model for registration, with 
the point in the LiDAR space expressed by its parametric form. such a map relation can be viewed as the mathematical model which 
registers the image pixels to point clouds. This model is not only suitable for a single image registration but also applicable to 
multiple consecutive images. We also studied scale problem in image and point clouds registration, with scale problem is defined by 
the optimal corresponding between the image resolution and the density of point clouds. Test dataset includes the DMC images and 
point clouds acquired by the Leica ALS50 II over an area in Henan Prov., China. Main contributions of the paper includes: [1] an 
derived collinear equation is introduced by which a ground point is expressed by its parametric form, which makes it possible to 
replace point feature by linear feature, hence avoiding the problem that it is almost impossible to find a point in the point clouds 
which is accurately corresponds to a point in the image space; [2] least square method is used to calculate the registration 
transformation parameters and the unknown parameter 4 in the same time;[3] scale problem is analyzed semi-quantitatively and to 
the authors" best knowledge, it is the first time in literature that clearly defines the scale problem and carries out semi-quantitative 
analysis in the context of LiDAR data processing. 
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