Abstract
This paper presents a fast and accurate method for matching oblique aerial image pairs. In order to achieve accurate matching results, we must consider viewpoint differences between the input images in addition to rotation and scaling. Existing methods that match aerial image pairs with viewpoint differences undergo heavy computation and have difficulty finding correspondences. In this paper, we propose a homography matrix evaluation method based on a geometric approach to increase the accuracy of image matching results. In addition, we achieve faster matching through an iterative transform simulation that reduces computational complexity. Experimental results show that the proposed method improves aerial image matching in terms of computational efficiency while achieving successful matching results.
Original language | English |
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Pages (from-to) | 317-331 |
Number of pages | 15 |
Journal | Pattern Recognition |
Volume | 87 |
DOIs | |
Publication status | Published - 2019 Mar |
Bibliographical note
Funding Information:This work was supported by the Agency for Defense Development ( ADD ) and Defense Acquisition Program Administration ( DAPA ) of Korea ( UC160016FD ). Partial support was also provided by Institute for Information and communications Technology Promotion ( IITP ) grant funded by the Korea government(MSIT) (No. 2017-0-01779 , A machine learning and statistical inference framework for explainable artificial intelligence).
Publisher Copyright:
© 2018 Elsevier Ltd
Keywords
- Aerial image
- Feature matching
- Homography matrix
- SIFT descriptor
- Viewpoint change
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence