1. Robust and Precise Registration of Oblique Images Based on Scale-Invariant Feature Transformation Algorithm
- Author
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Yang Huachao, Wang Yongbo, and Zhang Shubi
- 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 - 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.
- Published
- 2012
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