Image Matching Method based on Harris Wavelet Algorithm and Sift Algorithm

In order to solve the problem of image self similarity or symmetry sift matching stability is not high, this paper proposes an image matching method combining SIFT algorithm with Harris Wavelet algorithm. To solve the problem that SIFT features extract more pseudo points and unstable points from rich texture images and affect image matching, a local invariant feature image matching method based on Harris threshold criterion is proposed Algorithm. On the basis of extracting SIFT invariant features, the algorithm uses Harris threshold criterion to select the extracted invariant features, and eliminates a large number of feature points with poor distinguishability in the image region, thus obtaining relatively stable and better distinguishable feature points. Secondly, the method of invariant feature vector and graph transformation matching (GTM) is used to accurately match the extracted stable feature points. The experimental results show that the efficiency and robustness of image matching can be enhanced by obtaining stable feature points and combining with a good matching strategy.