Name
Abstract | ||
|---|---|---|
Registration between multimodal images is carried out using mutual information (MI) as a similarity measure. MI registration does not require linearity between two images; therefore, this method is effective in registration between multimodal images. First, corresponding points between multiband images are obtained in sub-pixel level. We evaluated the sub-pixel registration errors between two images. In this case, MI shows more accurate performance than sum square distance (SSD) and normalized cross-correlation (NCC). This result shows that the technique is robust with respect to variants of illumination or wavelength of observation band. Second, image-to-map registration is also successful. These results proved the potential of MI to build GIS with satellite images and map data. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IGARSS.2011.6049854 | Geoscience and Remote Sensing Symposium |
Keywords | Field | DocType |
image registration,GIS,image-to-map registration,map data,multiband images,multimodal images,mutual information,normalized cross-correlation,registration technique,satellite images,similarity measure,subpixel registration errors,sum square distance,Image-Map Registration,Mutual Information,Sub-pixel Estimation | Cross-correlation,Computer vision,Normalization (statistics),Similarity measure,Pattern recognition,Computer science,Image matching,Remote sensing,Linearity,Artificial intelligence,Mutual information,Image registration | Conference |
ISSN | ISBN | Citations |
2153-6996 | 978-1-4577-1003-2 | 0 |
PageRank | References | Authors |
0.34 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryosuke Mashiko | 1 | 0 | 0.34 |
| akira iwasaki | 2 | 193 | 16.71 |