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Robust and Precise Registration of Oblique Images Based on Scale-Invariant Feature Transformation Algorithm
- Source :
- IEEE Geoscience and Remote Sensing Letters. 9:783-787
- Publication Year :
- 2012
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2012.
-
Abstract
- The automatic registration of oblique images taken at different viewpoints remains a challenge until today. Based on scale-invariant feature transformation (SIFT) algorithm, a robust and accurate weighted least square matching (LSM) (SIFT/LSM) method modeled using 2-D projective transformation is proposed for highly accurate registration of oblique images. Normalized cross correlation (NCC) metric modified by an adaptive scale and orientation of SIFT features (SIFT/NCC) is proposed to obtain a good initial estimation for the SIFT/LSM. For practical use, image matching is implemented using a coarse-to-fine multistage strategy by sequentially incorporating the standard SIFT algorithm, SIFT/NCC, and SIFT/LSM. Experiments conducted on oblique images of real-world scenes demonstrate the feasibility of the proposed approach.
- Subjects :
- Cross-correlation
Image matching
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Image registration
Oblique case
Scale-invariant feature transform
Feature transformation
Pattern recognition
Scale invariance
Geotechnical Engineering and Engineering Geology
Robustness (computer science)
Computer vision
Artificial intelligence
Electrical and Electronic Engineering
business
Algorithm
Mathematics
Subjects
Details
- ISSN :
- 15580571 and 1545598X
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Geoscience and Remote Sensing Letters
- Accession number :
- edsair.doi...........64c395168212ea77c8555320b21e8b4d
- Full Text :
- https://doi.org/10.1109/lgrs.2011.2181485