Image registration is required in many remote sensing applications such as multispectral classification, environmental
monitoring, change detection, etc. In this paper, a novel approach of automatic registration of optical remote sensing
images based on SURF (Speed Up Robust Features) and NSNNI (Nearest and Second-Nearest Neighbors Iterative
Matching) is proposed. Using SURF's detector and descriptor, we can generate scale and rotation invariant control points.
Then, the efficient NSNNI method is used to simultaneously find correct matching point pairs and obtain precise
transform model. The results of experiments show that our method can achieve sub-pixel accuracy and satisfy the
real-time demand.
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