Registrating oblique images by integrating affine and scale-invariant features. Issue 10 (19th May 2018)
- Record Type:
- Journal Article
- Title:
- Registrating oblique images by integrating affine and scale-invariant features. Issue 10 (19th May 2018)
- Main Title:
- Registrating oblique images by integrating affine and scale-invariant features
- Authors:
- Yu, Mei
Yang, Huachao
Deng, Kazhong
Yuan, Kai - Abstract:
- ABSTRACT: Automatic registration of oblique images can be challenging due to the complexly geometric deformations of the images. A feature-based registration method for oblique images is proposed in this study. The proposed method integrates affine and scale-invariant features and mainly includes three steps: initial matching, propagative matching, and final registration. In the initial matching, the maximally stable extremal region (MSER) keypoints are detected and matched based on Scale-Invariant Feature Transform (SIFT) descriptors. The SIFT keypoints in the supporting region (SR) of MSER are matched using affine invariant normalized cross-correlation matching algorithm. Neighbourhood supporting strength – the ratio of SIFT matches to SIFT keypoints in SR, is proposed to eliminate error matches. In propagative matching, the matches in the former step are used for coarse geometric transformation estimation. The keypoints that have not been successfully matched in the initial matching are handled by iterative correspondence identification under geometric constraint. The two matching processes obtain evenly distributed and sufficient number of correspondences to calculate the accurate transformation between inputted images. Final registration is achieved using bilinear interpolation on sensed image. Experimental results carried on close-range, satellite, and aerial images demonstrate that the proposed method can achieve reliable correspondences and performs better thanABSTRACT: Automatic registration of oblique images can be challenging due to the complexly geometric deformations of the images. A feature-based registration method for oblique images is proposed in this study. The proposed method integrates affine and scale-invariant features and mainly includes three steps: initial matching, propagative matching, and final registration. In the initial matching, the maximally stable extremal region (MSER) keypoints are detected and matched based on Scale-Invariant Feature Transform (SIFT) descriptors. The SIFT keypoints in the supporting region (SR) of MSER are matched using affine invariant normalized cross-correlation matching algorithm. Neighbourhood supporting strength – the ratio of SIFT matches to SIFT keypoints in SR, is proposed to eliminate error matches. In propagative matching, the matches in the former step are used for coarse geometric transformation estimation. The keypoints that have not been successfully matched in the initial matching are handled by iterative correspondence identification under geometric constraint. The two matching processes obtain evenly distributed and sufficient number of correspondences to calculate the accurate transformation between inputted images. Final registration is achieved using bilinear interpolation on sensed image. Experimental results carried on close-range, satellite, and aerial images demonstrate that the proposed method can achieve reliable correspondences and performs better than state-of-the-art methods for oblique image registration. … (more)
- Is Part Of:
- International journal of remote sensing. Volume 39:Issue 10(2018)
- Journal:
- International journal of remote sensing
- Issue:
- Volume 39:Issue 10(2018)
- Issue Display:
- Volume 39, Issue 10 (2018)
- Year:
- 2018
- Volume:
- 39
- Issue:
- 10
- Issue Sort Value:
- 2018-0039-0010-0000
- Page Start:
- 3386
- Page End:
- 3405
- Publication Date:
- 2018-05-19
- Subjects:
- Remote sensing -- Periodicals
Télédétection -- Périodiques
621.3678 - Journal URLs:
- http://www.tandfonline.com/toc/tres20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01431161.2017.1362129 ↗
- Languages:
- English
- ISSNs:
- 0143-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.528000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 18609.xml