关键词: 卷积神经网络（CNN）, 图像配准, 十字点集, 遥感影像拼接

Abstract: Image registration and coordinate transformation are two important processes of remote sensing image mosaic in different backgrounds, which are studied respectively in this paper. Focused on the image registration, a method based on hierarchical convolutional features is proposed. This method adaptively obtains image features from CNN（Convolutional Neural Networks） and then sends the features derived from different images in different depth to CF（Correlation Filter） to compute the similarity between them. Therefore the locations of the feature points are computed with considering the different depth hierarchical convolutional features. In order to simplify the coordinate transform method, the cross points method is proposed. According to the feature points location from the image registration, the transform parameters can be computed. Then the remote sensing images can be mosaicked by converting all pixels from one image to another. The experimental results show the effectiveness and robustness of the proposed method by comparing to traditional mosaic method based on SIFT（Scale Invariant Feature Transform）.

Key words: Convolutional Neural Networks（CNN）, image registration, cross points, remote sensing image mosaic