What are the collocation methods?

There are many methods of image matching, which are generally divided into two categories, one is based on gray matching, and the other is based on feature matching.

(1) method based on gray matching. Also known as correlation matching algorithm, the spatial two-dimensional sliding template is used for image matching, and the difference between different algorithms is mainly reflected in the selection of template and correlation criteria.

② Method based on feature matching. Firstly, the features are extracted from the original image, and then the matching relationship between the features of the two images is established. Commonly used feature matching primitives include salient features such as points, lines and regions. Compared with the number of pixels, the number of image features is much less, and the matching metric between features changes dramatically with the position, so it is easy to find the accurate matching position. Feature extraction can greatly reduce the influence of noise and has strong adaptability to gray level change, deformation and occlusion.

The task of image matching is to find the corresponding relationship between pixels in two or more images of the same scene. The image matching method we study is mainly based on image features, which mainly includes three steps: feature extraction, feature description and feature matching. SIFT method is a classic matching method with good effect at present. In our research process, SIFT method is used as a benchmark to evaluate our proposed algorithm.