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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Goncalves, H. Corte-Real, L. Goncalves, J.A. |
| Copyright Year | 1980 |
| Abstract | Automatic image registration (AIR) is still a present challenge for the remote sensing community. Although a wide variety of AIR methods have been proposed in the last few years, there are several drawbacks which avoid their common use in practice. The recently proposed scale invariant feature transform (SIFT) approach has already revealed to be a powerful tool for the obtention of tie points in general image processing tasks, but it has a limited performance when directly applied to remote sensing images. In this paper, a new AIR method is proposed, based on the combination of image segmentation and SIFT, complemented by a robust procedure of outlier removal. This combination allows for an accurate obtention of tie points for a pair of remote sensing images, being a powerful scheme for AIR. Both synthetic and real data have been considered in this work for the evaluation of the proposed methodology, comprising medium and high spatial resolution images, and single-band, multispectral, and hyperspectral images. A set of measures which allow for an objective evaluation of the geometric correction process quality has been used. The proposed methodology allows for a fully automatic registration of pairs of remote sensing images, leading to a subpixel accuracy for the whole considered data set. Furthermore, it is able to account for differences in spectral content, rotation, scale, translation, different viewpoint, and change in illumination. |
| Sponsorship | IEEE Geoscience and Remote Sensing Society IEEE URSI |
| Starting Page | 2589 |
| Ending Page | 2600 |
| Page Count | 12 |
| File Size | 1049836 |
| File Format | |
| ISSN | 01962892 |
| Volume Number | 49 |
| Issue Number | 7 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Remote sensing Satellites Feature extraction Histograms Pixel Image registration scale invariant feature transform (SIFT) Automatic image registration (AIR) image segmentation optical images |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences Electrical and Electronic Engineering |
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