Multiresolution Image Registration Using Spatial Mutual Information
The maximization of mutual information has been very successful at the registration of images. Unfortunately, mutual information takes only into account the relationship between individual pixels and not those of each pixel's neighborhood. Mutual information ignores spatial information. In this...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/9145 |
| _version_ | 1848745865358868480 |
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| author | Amankwah, Anthony Aldrich, Chris |
| author2 | IEEE |
| author_facet | IEEE Amankwah, Anthony Aldrich, Chris |
| author_sort | Amankwah, Anthony |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The maximization of mutual information has been very successful at the registration of images. Unfortunately, mutual information takes only into account the relationship between individual pixels and not those of each pixel's neighborhood. Mutual information ignores spatial information. In this paper, we propose a new similarity metric called enhanced mutual information (EMI), which combines mutual information with a weighting function based on the absolute difference of corresponding pixel values. In order to reduce computational cost we also use multiresolution wavelet decomposition as a search data strategy. Experimental results show that the enhanced mutual information is not only more robust to noise than mutual information but more reliable in the registration of multitemporal images. |
| first_indexed | 2025-11-14T06:24:09Z |
| format | Conference Paper |
| id | curtin-20.500.11937-9145 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:24:09Z |
| publishDate | 2012 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-91452017-09-13T16:02:18Z Multiresolution Image Registration Using Spatial Mutual Information Amankwah, Anthony Aldrich, Chris IEEE image registration Mutual Information Enhanced Mutual Information Wavelets The maximization of mutual information has been very successful at the registration of images. Unfortunately, mutual information takes only into account the relationship between individual pixels and not those of each pixel's neighborhood. Mutual information ignores spatial information. In this paper, we propose a new similarity metric called enhanced mutual information (EMI), which combines mutual information with a weighting function based on the absolute difference of corresponding pixel values. In order to reduce computational cost we also use multiresolution wavelet decomposition as a search data strategy. Experimental results show that the enhanced mutual information is not only more robust to noise than mutual information but more reliable in the registration of multitemporal images. 2012 Conference Paper http://hdl.handle.net/20.500.11937/9145 10.1109/OCEANS.2012.6404780 IEEE restricted |
| spellingShingle | image registration Mutual Information Enhanced Mutual Information Wavelets Amankwah, Anthony Aldrich, Chris Multiresolution Image Registration Using Spatial Mutual Information |
| title | Multiresolution Image Registration Using Spatial Mutual Information |
| title_full | Multiresolution Image Registration Using Spatial Mutual Information |
| title_fullStr | Multiresolution Image Registration Using Spatial Mutual Information |
| title_full_unstemmed | Multiresolution Image Registration Using Spatial Mutual Information |
| title_short | Multiresolution Image Registration Using Spatial Mutual Information |
| title_sort | multiresolution image registration using spatial mutual information |
| topic | image registration Mutual Information Enhanced Mutual Information Wavelets |
| url | http://hdl.handle.net/20.500.11937/9145 |