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| Content Provider | Springer Nature Link |
|---|---|
| Author | Zhou, ZeMing Ma, Ning Li, YuanXiang Yang, PingLü Zhang, Peng Li, YunYing |
| Copyright Year | 2014 |
| Abstract | The Pan-sharpening approach based on principle component analysis (PCA) is affected by severe spectral distortion. To address this problem, a new pan-sharpening model based on PCA and variational technique is proposed to construct the substitute image of the first principal component (PC1). The energy functional consists of three terms. The first term injects PC1 with the geometric structure of the panchromatic (Pan) image. The second term preserves the spectral pattern of the multi-spectral image in the merged result. And the third term guarantees the smoothness of the functional optimization solution. The fusion result is given by the minimum of the energy functional, which is computed with the gradient descend flow. The experiments on QuickBird and IKONOS datasets validate the effectiveness of the proposed model. Compared with the state-of-the-art pan-sharpening approaches, this model exhibits a better trade-off between improving spatial quality and preserving spectral signature of the MS image. |
| Starting Page | 1 |
| Ending Page | 10 |
| Page Count | 10 |
| File Format | |
| ISSN | 1674733X |
| Journal | Science in China Series : Information Sciences |
| Volume Number | 57 |
| Issue Number | 11 |
| e-ISSN | 18691919 |
| Language | English |
| Publisher | Science China Press |
| Publisher Date | 2014-09-05 |
| Publisher Place | Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | PCA variational PCA fusion remote sensing image pan-sharpening gradient descend flow Information Systems and Communication Service |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science |
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