The application scope of 3D laser scanning technology is gradually expanding, but the lack of real texture information in laser point clouds results in deviation between target detail reconstruction and actual targets. 3D visualization digital imaging technology can effectively compensate for the shortcomings of 3D laser scanning technology. How to effectively integrate and apply it has become a key research direction, Therefore, a study on the 3D visualization digital image fusion target detail reconstruction method of GeoSLAM laser point cloud is proposed. Using the point cloud filtering algorithm to remove noise information from the GeoSLAM laser point cloud, and correcting and processing the distortion phenomenon of 3D visualization digital images, based on this, the Moravec operator is used to extract the detailed feature points of the fusion target, register the feature points in the laser point cloud and digital images, and develop the fusion target detail reconstruction program, thus achieving effective fusion of the laser point cloud and digital images, that is, precise reconstruction of the target details. The experimental results show that: Compared with the comparison methods, the proposed method can complete the detail reconstruction more accurately. It has an average correlation coefficient of 0.929 5, and a lower error rate of detail feature point extraction of the fusion target. The detail reconstruction effect of the digital image of the architectural category is better, and the error rate of detail feature point extraction is only 1%, which fully confirms the better application performance of the proposed method.