Matching Approach for Multi-sensor Images with Affine Deformation

A rapid and robust approach is proposed to match multi-sensor images in affine space. Firstly, valid sub-regions are automatically selected from the small image based on 2-dimensional Moran information. Then, similarity map between each valid sub-region and the large image is calculated by gradient orientation correlation in translation space. The translation similarity maps are transformed and combined to appropriate the affine similarity. Finally, matching result is obtained by finding the maximum value of combined map in affine space. The proposed approach avoids affine transformation and image comparison which always execute many times in traditional affine matching approach, and has a comparatively low computing complexity as traditional translation matching method. Experiments show that our approach not only runs fast, but also has higher matching rate than other methods.