Paper Info
Title
Automatic co-registration of satellite imagery and LiDAR data using local Mutual Information
Abstract
Automatic co-registration is a basic step in multi-sensor data fusion for remote sensing applications. The effectiveness of Mutual Information (MI) as a similarity measure for multi-sensor image registration has previously been reported for medical and remote sensing applications. In this paper, a new intensity-based approach built on local MI principles is presented. The approach decreases the complexity of higher dimension optimization by measuring local MI on well-distributed tie points. In addition, the reliability of registration is improved due to utilization of redundant observations of similarity. The performance of the proposed method for the registration of WorldView2 satellite imagery with LiDAR elevation and intensity data has been experimentally evaluated and the results obtained are presented.
Year
DOI
Venue
2013
10.1109/IGARSS.2013.6721356
Geoscience and Remote Sensing Symposium
Keywords
Field
DocType
geophysical image processing,geophysical techniques,image registration,optical radar,remote sensing by laser beam,LiDAR data,LiDAR elevation data,LiDAR intensity data,WorldView2 satellite imagery,local mutual information,multisensor data fusion,multisensor image registration,remote sensing applications,satellite imagery automatic co-registration,LiDAR,Mutual Information,Registration,satellite imagery
Computer vision,Satellite imagery,Similarity measure,Computer science,Remote sensing,Remote sensing application,Sensor fusion,Lidar,Artificial intelligence,Mutual information,Elevation,Image registration
Conference
ISSN
ISBN
Citations 
2153-6996
978-1-4799-1114-1
0
PageRank 
References 
Authors
0.34
5
4
Name
Order
Citations
PageRank
Ebadat G. Parmehr121.39
Clive Fraser213415.09
Chunsun Zhang3264.37
Joseph Leach421.05