A REMOTE SENSING IMAGERY AUTOMATIC FEATURE REGISTRATION METHOD BASED ON MEAN-SHIFT

Remote sensing image feature matching is a research hotspot in the remote sensing imagery processing. The existing algorithms maybe extract more feature points than need in fact, and should be improved in feature extraction and distribution control. In this Paper, we proposed a new method which reference object-oriented processing theory. After extract the local-Invariant feature points by SIFT, We split the two images into multi-scale objects by mean-shift segmentation. With removing the non-feature point of the surface features objects, we establish the affine transformation relations between all the useful objects using the constraints such as the angle constraints. Final we got the matching feature points set and find the affine transformation modal by the RANSAC method. UAV imaging experiments show that this method can guarantee the accuracy and effective.