Name
Title | ||
|---|---|---|
An Effective Histogram Binning For Mutual Information Based Registration Of Optical Imagery And 3d Lidar Data |
Abstract | ||
|---|---|---|
Automatic registration of multi-sensor data is a basic step in data fusion applications. Mutual information (MI) has been widely used in medical and remote sensing image registration. In this paper, an effective histogram binning technique is proposed to improve the robustness of image registration using MI and Normalized MI (NMI). Increasing the bin size improves the robustness of MI to local maxima that occur in the convergence surface of MI. In addition, the computation cost of registration is decreased due to use of a smaller joint pdf, without decreasing the accuracy. The performance of the proposed method in the registration of aerial imagery with LiDAR data has been experimentally evaluated and the results obtained are presented. |
Year | Venue | Keywords |
|---|---|---|
2013 | 2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013) | Mutual information, registration, LiDAR, optical imagery |
Field | DocType | ISSN |
Computer vision,Histogram,Normalization (statistics),Pattern recognition,Computer science,Robustness (computer science),Maxima and minima,Sensor fusion,Lidar,Artificial intelligence,Mutual information,Image registration | Conference | 1522-4880 |
Citations | PageRank | References |
1 | 0.35 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ebadat G. Parmehr | 1 | 2 | 1.39 |
| Clive Fraser | 2 | 134 | 15.09 |
| Chunsun Zhang | 3 | 26 | 4.37 |
| Joseph Leach | 4 | 2 | 1.05 |