Image Registration plays a very important role in the field of remote sensing. In order to have a better registration quality and make the automatization possible, choos ing and matching the control points from conjugate images become very important. In fact, the control points required for image registration should have following three key factors, that is, the amount, validity and distribution of control points.
¡@¡@In the study, we take QuickBird Satellite Images as the main ones; on the other hand, it conducts two groups of image registrations resulted from aerial images at various times. After detecting feature points using different algorithms, the study makes use of feature matching methods to get conjugate points between two overlapped images. The algorithms used above are SIFT, ASIFT and MESR. SIFT is an algorithm which invariant to scales, rotation, affine stretch and change in brightness. ASIFT undertakes simulations based on the theory of SIFT and thus carries out fully affine invariant. The feature points obtained from MSER have physical meaning in its location. By using feature matching algorithms like K-d tree and BBF, the matched feature points from two overlapped images would be turned into the conjugate points which can be control points for image registration.
¡@¡@During the process of image preprocessing, it is learned that the feature points detected by SIFT and MSER through feature matching are very few. Hence, this study attempts to employ histogram specification¡Bcontrast stretching and scale change methods to see if it is helpful to the feature detections and matching through change of image quality and image size. The experiment found that scale change will improve both the amount and accuracy of conjugate points detected by different algorithms. When considering distribution of the feature points, the study takes advantage of image cropping approach to conduct feature detections and matching individually. It is found that more conjugate points with uniform distribution can be obtained via image cropping technique.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-1022110-093813 |
| Date | 22 October 2010 |
| Creators | Tseng, Jen-ping |
| Contributors | Ming-Jer Huang, Tien-Yuan Shih, Yi-Hsin Tseng, Liang-Hui Lee, Shiahn-Wern Shyue |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1022110-093813 |
| Rights | withheld, Copyright information available at source archive |
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