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Automatic remote sensing image registration has achieved great accomplishment. However, it is still a vital challenging problem to develop a robust and accurate registration method due to the negative effects of noise and imaging differences between images. For these images, it is difficult to guarantee the accuracy and robustness at the same time for one-step registration methods. To address this issue, we introduce an effective coarse-to-fine strategy and develop a new two-step registration method based on deep and local features in this paper. The first step is to calculate the approximate spatial relationship, which is obtained by a convolutional neural network. This step makes full use of the deep features to match and can generate stable results. For the second step, a matching strategy considering spatial relationship is applied to the local feature-based method. In addition, this step adopts more accurate …