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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wang Wantong Li Yuling Zhao Qingliang |
| Copyright Year | 2012 |
| Abstract | To resolve multi-sensor remote sensing images registration, a new approach which combines feature and regional similarity measure is proposed. This approach firstly adopts SIFT algorithm to match feature points and constructs initial affine transformation function; next uses normalized cross-correlation coefficient (NCC) to define regional similarity measure, and improves NCC with initial affine transformation parameters in order to get further matching points from those unmatched in SIFT algorithm. Then, after gross filtering the effective matching feature points, builds the model for image registration by all the matching feature points. This method combines the advantages of feature matching and regional matching, and solves the problem that the multi-sensor remote sensing images are difficult to match correctly because of geometric and radiometric differences. Experiments show that this method has strong robustness, and are of higher registration accuracy than single registration method. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 661348 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467308724 |
| e-ISBN | 9781467308755 |
| DOI | 10.1109/RSETE.2012.6260357 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-01 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image registration Accuracy Correlation Feature extraction Educational institutions Vectors Remote sensing |
| Content Type | Text |
| Resource Type | Article |
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