Multimodal remote sensing image registration based on adaptive multi-scale PIIFD

In recent years, due to the wide application of multi-sensor vision systems, multimodal image acquisition technology has continued to develop. Monomodal images cannot meet the needs of image analysis, which requires image fusion and stitching to process images for better image analysis. Image registration is an important prerequisite of image fusion and stitching. Most of the existing multimodal image registration methods are only suitable for two modalities, and cannot uniformly register multimodal image data. Therefore, this paper proposes a multimodal remote sensing image registration method based on adaptive multi-scale PIIFD (AM-PIIFD). This method extracts KAZE features in the scale space constructed by nonlinear diffusion filtering. It can effectively preserve the edge feature information while filtering out the noise. Then, the proposed AM-PIIFD feature descriptor is used to describe the multi-scale features. Finally, according to the consistency of the feature main orientation, most of the mismatches are removed, and the image alignment transformation is realized. The qualitative and quantitative comparisons with the other three advanced methods show that our method can achieve good performance in multimodal remote sensing image registration.