A robust feature-based registration method of multimodal image using phase congruency and coherent point drift
2013
This paper presents a new feature matching algorithm for nonrigid multimodal image registration. The proposed
algorithm first constructs phase congruency representations (PCR) of images to be registered. Then scale invariant
feature transform (SIFT) method is applied to capture significant feature points from PCR. Subsequently, the putative
matching is obtained by the nearest neighbour matching in the SIFT descriptor space. The SIFT descriptor is then
integrated into Coherent Point Drift (CPD) method so that the appropriate matching of two point sets is solved by
combining appearance with distance properties between putative match candidates. Finally, the transformation estimated
by matching the point sets is applied to registration of original images. The results show that the proposed algorithm
increases the correct rate of matching and is well suited for multi-modal image registration.
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