A Novel Robust Feature Descriptor for Multi-Source Remote Sensing Image Registration

Non-linear radiation difference (NRD) will lead to the corresponding features cannot be mapped one by one, so the traditional image feature matching methods based on intensity or gradient fail to be directly applied to the multisource remote sensing image registration. In this paper, a new robust feature descriptor is proposed, which has the invariance of radiation, scale and rotation. The nonlinear diffusion function which is insensitive to the radiation difference is used to construct the scale space so that the descriptors can be used in images with different resolutions. A pixel-by-pixel local phase congruency algorithm is used to extract the corresponding points, and then the features are described by means of rotation invariance description. Feature matching is completed based on feature vector constructed by the descriptor, thus to realize image registration. In the experimental part, three kinds of multisource remote sensing images with large radiation differences were used to test the descriptors. The results showed that the proposed method effectively extracted the corresponding features, and achieved the best effect in the quantitative evaluation of image registration.