Abstract: The extraction of mosaic lines is an important step in the mosaic of remote sensing images. To address the problems related to mosaic line extraction existing in current mosaic techniques of high-resolution remote sensing images, the authors propose a mosaic line extraction method based on multi-scale segmentation and the A* algorithm and the steps are as follows. First, pre-segment the overlapping regions of images using the simple linear iterative cluster (SLIC) algorithm, and conduct the clustering of regions with notable surface features to generate compact superpixels to obtain and extract the texture information of the surface features in the images. Then, merge the adjacent regions by continuously increasing the regional dissimilarity threshold while recording the region merging process using a scale set model. Meanwhile, determine the optimal segmentation scale according to the local variance of spectral characteristics and the Moran index to solve the problem of over-segmentation. Finally, find out the best mosaic lines on the segmentation paths using the A* algorithm. Experimental results prove that this method can effectively solve the problem that mosaic lines pass through distinct areas such as buildings, farmlands, and rivers, thus reducing splicing traces. Meanwhile, the optimal segmentation scale can be effectively selected by recording the merging process using a scale set model. Therefore, the mosaic line extraction method proposed in this study can be widely applied in the mosaic of high-resolution remote sensing images and is practically significant for the automatic mosaic of remote sensing images.