In this study, an imaging system combining cameras and rotating Risley prisms is proposed to address the difficulty of considering the field of view and spatial resolution in a target scene’s three-dimensional (3D) reconstruction. The imaging system can form a virtual camera array under different Risley prism rotation angles, adjust the array virtual cameras’ imaging position using rail movement, and realize a subregional multiview image acquisition in a large field of view. A calibration approach of the array virtual camera’s internal and external parameters using a geometrical transformation relationship is proposed, and the subregional 3D point cloud acquisition approach based on the triangulation principle is established, employing the camera projection model and the double-prism refraction model. A prelocalization approach for overlapping regions of multiview pictures is presented on this basis, and a coarse-to-precise subregional point cloud alignment fusion is obtained by integrating the iterative closest neighbor algorithm. The experimental results reveal that the proposed imaging system can achieve largescale and high-resolution 3D target reconstruction and can ensure a 3D reconstruction accuracy due to the coarse-to-precise point cloud alignment approach while enhancing processing efficiency.