Paper Info
Title
Shadow-Based Hierarchical Matching for the Automatic Registration of Airborne LiDAR Data and Space Imagery.
Abstract
The automatic registration of LiDAR data and optical images, which are heterogeneous data sources, has been a major research challenge in recent years. In this paper, a novel hierarchical method is proposed in which the least amount of interaction of a skilled operator is required. Thereby, two shadow extraction schemes, one from LiDAR and the other from high-resolution satellite images, were used, and the obtained 2D shadow maps were then considered as prospective matching entities. Taken as the base, the reconstructed LiDAR shadows were transformed to image shadows using a four-step hierarchical method starting from a coarse 2D registration model and leading to a fine 3D registration model. In the first step, a general matching was performed in the frequency domain that yielded a rough 2D similarity model that related the LiDAR and image shadow masks. This model was further improved by modeling and compensating for the local geometric distortions that existed between the two heterogeneous data sources. In the third step, shadow masks, which were organized as segmented matched patches, were the subjects of a coinciding procedure that resulted in a coarse 3D registration model. In the last hierarchical step, that model was ultimately reinforced via a precise matching between the LiDAR and image edges. The evaluation results, which were conducted on six datasets and from different relative and absolute aspects, demonstrated the efficiency of the proposed method, which had a very promising accuracy on the order of one pixel.
Year
DOI
Venue
2016
10.3390/rs8060466
REMOTE SENSING
Keywords
Field
DocType
3D registrations,shadows,LiDAR,HRSI (High Resolution Satellite Imagery),automatic matching
Frequency domain,Computer vision,Shadow,Satellite,Remote sensing,Shadow mapping,Lidar,Operator (computer programming),Artificial intelligence,Pixel,Lidar data,Geology
Journal
Volume
Issue
Citations 
8
6
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Alireza Safdarinezhad110.72
Mehdi Mokhtarzade2718.10
Mohammad Javad Valadan Zoej36510.19