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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Barbu, A. Ionasec, R. |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Statistics, Florida State University, Tallahassee, 32306, USA (Barbu, A.) || Siemens Corporate Research, 755 College Rd. E, Princeton, NJ 08540, USA (Ionasec, R.) |
| Abstract | Cross-modality image registration is a difficult problem because the same structures have different intensity patterns in the two modalities, making straightforward methods based on SSD or cross-correlation not applicable. This paper presents a learning based approach to cross-modality image registration. First, it describes a method to map the image registration problem into a problem of binary classification. Then, it presents a method to select a number of image registration algorithms from a larger pool and combine them by AdaBoost into a boosted algorithm that is more accurate than any of the algorithms in the pool. Finally, it presents a method named virtual boosting that allows to directly obtain the result of the boosted algorithm without performing any parameter search. In our cross-modality image registration application, the algorithm pool consists of many feature-based registration algorithms with different configurations. An experimental validation on the registration of thousands of aerial video frames with satellite images from Google Maps showed that the boosted algorithm has a 20–30% smaller error than the best registration algorithm from the pool (based on SIFT features). More generally, the method presented can be applied to combine a number of algorithms aimed at solving the same problem into a boosted algorithm that is more accurate than any of them. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 6285256 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424434602 |
| DOI | 10.1109/URS.2009.5137482 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Phase noise Image registration Satellites Surveillance Video sequences Boosting Educational institutions Statistics Global Positioning System Biomedical imaging |
| Content Type | Text |
| Resource Type | Article |
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